Reactor Design for Partial Upgrading of Bitumen Via Aquaprocessing

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2018-12-27 Reactor Design for Partial Upgrading of Bitumen via Aquaprocessing

Gill, Sukhdeep Singh

Gill, S. S. (2018). Reactor Design for Partial Upgrading of Bitumen via Aquaprocessing (Unpublished master's thesis). University of Calgary, Calgary, AB. http://hdl.handle.net/1880/109845 master thesis

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UNIVERSITY OF CALGARY

Reactor Design for Partial Upgrading of Bitumen via Aquaprocessing

Sukhdeep Singh Gill

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE

GRADUATE PROGRAM IN CHEMICAL ENGINEERING

CALGARY, ALBERTA

DECEMBER, 2018

Abstract

Alberta oil industry is facing a major challenge because of the widening price differentials between West Texas Intermediate and Western Canadian Select. The Western Canadian Select is trading at low of US$ 16.71 /bbl. because of its high viscosity, density, total acid number, and sulfur content and lack of access to market outside North America. Under these circumstances, partial upgrading processes such as Aquaprocessing are envisioned as a potential solution. The synthetic crude oil produced from Aquaprocessing of bitumen requires 50 vol.% less diluents than the Athabasca bitumen to meet the pipeline specifications. This thesis is focused on evaluating the reactor design parameters required for scale up of this technology. The kinetic parameters for hydrocracking reaction were calculated using first order rate law expression for the packed bed reactor. Diffusivity of steam in bitumen, dimensionless numbers and hydrodynamic properties of the fluid inside the reactor were calculated using experimental and simulated data. The experimental results indicate that the effect of catalyst particle size depends on the catalyst preparation techniques. The steam diffusivity in bitumen was found to increase linearly with increase in reaction temperature. 0.05 psi/m pressure drop and 39 vol.% liquid holdups are predicted for the two-phase flow regime.

Preface

This thesis is original, unpublished, independent work by the author, Sukhdeep Singh Gill.

iii

Acknowledgements

First, I would like to thank Dr. Pedro Pereira-Almao who believed in me and gave for this exceptional opportunity to work in his team. It was an honor to work under his leadership and learn from him. I am indebted to Dr. Pereira for this lifetime opportunity to pursue my dream.

Thanks to Dr. Venkataraman Thangadurai from Department of Chemistry at University of

Calgary and Dr. Xiaohui Zhang & John Evans from Shell Canada for encouraging me to pursue this goal.

My sincere thanks to Dr. Suresh Mulmi, Dr. Gerardo Vitale, Dr. Lante Carbognani, Dr. Josefina

Scott, Dr. Carlos Scott, Alejandro Coy, Eduardo Garcia, Dr. Azfar Hassan and Dr. Monica

Bartolini for their encouragement, constructive feedbacks and being always accessible when needed. I would like to thank Mike Grigg from Electronics and Instrument department for his help with LabVIEW programming.

A special thanks to Jose Luis and Dr. Khaled Omar for their help during pilot plant construction.

Thanks to Dr. Suresh Mulmi for In-situ XRD and TGA experiments and continuous support throughout my university career.

It has been my pleasure to be a part of CAFÉ group. Thanks Tatiana, Violeta, Mariana, Maria,

Diego, Jose, Omar, Alejandro, Eduardo, Josune, Christian, Juan Carlos, Ghada, Erika, Fahad,

Vahideh, Mysam, Mina and many more for creating a friendly and safe working environment.

My sincere thanks to all the members of Shell Technology Centre Calgary for being an excellent support.

I apologize to my parents andmy brothers; Randeep, Mandeep and Navdeep for being so busy and missing most of the family events. I owe you guys.

Dedication

To Jaspreet

Pawan Guru Pani Pitta Mata Dhartmahat Air as Teacher Water as Father Mother as Great Earth Sri Guru Granth Sahib Ji

Table of Contents

Abstract ...... ii

Preface ...... iii

Acknowledgements ...... iv

Dedication ...... v

Table of Contents ...... vi

List of Tables ...... x

List of Figures ...... xi

List of Abbreviations ...... xii

List of Symbols ...... xiv

CHAPTER 1: Introduction ...... 1

1.1 Introduction ...... 1

1.2 Motivation and Objectives ...... 3

1.3 Thesis Organization...... 5

CHAPTER 2: Literature Review ...... 6

2.1 Crude Oil ...... 6

2.2 Bitumen Transportation...... 8

2.3 Upgrading ...... 9

2.3.1 Non-Catalytic Carbon Rejection ...... 10

2.3.1.1 Solvent De-Asphalting (SDA) ...... 10

2.3.1.2 Thermal Cracking/Coking...... 11

2.3.2 Hydrogen Addition ...... 13

2.3.2.1 Trickle Bed Reactor ...... 13

2.3.2.2 Fixed-Bed Reactor with Cocurrent Upflow ...... 14

2.3.2.3 Ebullated Bed Reactor ...... 14

2.3.2.4 Slurry Reactor ...... 14

2.4 Upgrading in Alberta ...... 15

2.5 Partial Upgrading ...... 16

2.6 Aquaprocessing ...... 16

2.6.1 Advances in Aquaprocessing ...... 18

2.7 Fixed-Bed Reactor with Cocurrent Upflow ...... 19

2.7.1 Process Chemistry ...... 20

2.7.2 Process Conditions ...... 24

2.7.3 Steps in Catalytic Reaction ...... 24

2.7.4 Packed Bed Reactor Design Equation ...... 25

2.7.5 Mass Transfer ...... 29

2.7.6 Flow regime ...... 30

2.7.7 Pressure Drop ...... 31

2.7.8 Gas and Liquid Holdup ...... 33

Chapter 3: Experimental Section ...... 34

3.1 Bitumen Feedstock ...... 34

3.2 Pilot Plant Setup ...... 35

3.2.1 Feed Section ...... 37

3.2.2 Reaction Section ...... 38

3.2.3 Separation Section ...... 39

3.3 Experimental Procedure ...... 39

vii

3.3.1 Reactor Filling ...... 39

3.3.2 Catalyst Treatment and Reduction ...... 40

3.3.3 Reaction Start-up ...... 41

3.3.4 Reaction Operation ...... 44

3.4 Analytic techniques ...... 44

3.4.1 Liquid Hydrocarbon Characterization ...... 44

3.4.2 Gas Analysis ...... 50

3.5 Catalyst Characterization ...... 51

3.5.1 Powered X-ray Diffraction (PXRD) ...... 51

3.5.2 Surface Area, Pore Size and Pore Volume ...... 52

3.5.3 Temperature Programmed Techniques ...... 54

3.5.4 Thermogravimetric Analysis (TGA) ...... 55

3.5.5 Metal analysis ...... 55

Chapter 4: Results and Discussion ...... 57

4.1 Catalyst Characterization ...... 57

4.2 Pilot Plant Operations...... 60

4.3 Thermal Run ...... 61

4.4 Catalytic Runs ...... 64

4.5 Kinetic Analysis for Hydrocracking* Reaction ...... 71

4.6 Mass Transfer Limitations ...... 76

4.7 Evaluation of Sensitivity Parameters ...... 78

4.8 Hydrodynamic Properties ...... 81

Chapter 5: Conclusions and Recommendations ...... 83

viii

5.1 Catalyst Particle Size and Preparation Technique ...... 83

5.2 Improvement in Synthetic Crude oil properties and Economic Advantage ...... 84

5.3 Packed Bed Reactor Design Equation ...... 84

5.4 Mass Transfer Limitation ...... 85

5.5 Hydrodynamics ...... 85

5.6 Recommendations ...... 86

References ...... 87

Appendix A ...... 96

HAZOP Review ...... 96

Appendix B ...... 99

Experimental Data ...... 99

Appendix C ...... 101

Difference between the product distribution for Cat H-2.1 and Cat J15...... 101

Appendix D ...... 102

Predicted Fluid Properties by ProMax at Reactor Conditions ...... 102

Appendix E ...... 107

Contributions ...... 107

Appendix F ...... 108

List of Tables

Table 1- 1: Petroleum Statistics of 2015(U.S. Energy Information Administration, 2017) ...... 2

Table 2- 2: Heavy Crude Oil Classification ...... 7

Table 2- 3: Pipeline Specifications (Keeson & Gieseman, 2018) ...... 8

Table 2- 4: List of Upgraders in Alberta ...... 15

Table 2- 5 : List of Partial-Upgrading Technologies ...... 17

Table 2- 6: Reactions Occurring During Aquaprocessing of Bitumen ...... 23

Table 2- 7: Optimized Operating Conditions ...... 24

Table 2- 8: Fukushima and Kusaka's Flow Regimes Equations ...... 31

Table 2- 9: Saada's Pressure Drop Equations ...... 32

Table 2- 10: Liquid Holdups in a Packed Bed Reactor with Cocurrent Upflow ...... 33

Table 3-1: JACOS Feedstock Properties ...... 34

Table 3- 2: Relative Error in Gas Composition for GC Analysis using TCD detector ...... 51

Table 4- 1: Textural Properties of the Catalysts ...... 58

Table 4- 2: Pilot Plant Test Program for Catalysts Performance Comparison ...... 61

Table 4- 3: Analytical Results for Thermal Run at 3.7 h Residence Time ...... 62

Table 4- 4: Tie-Back Period Results for Cat J17 ...... 71

Table 4- 5: Kinetic Rate Constants for Hydrocracking* of Vacuum Residue ...... 72

Table 4- 6: Kinetic Parameters for Hydrocracking of Vacuum Residue in Aquaprocessing ...... 74

Table 4- 7: Cat J17 Performance ...... 76

Table 4- 8: Evaluation of Mass Transfer Coefficient ...... 77

Table 4- 9: Schmidt Number at Different Reaction Temperatures ...... 80

Table 4- 10: Effect of Catalyst Particle Size on Hydrodynamic Properties ...... 82

List of Figures

Figure 1- 1: Energy per Capita vs. GDP per Capita (Rez, 2017) with permission ...... 1

Figure 1- 2:Alberta Oil Production (thousand bbl./day) (Oil Sands magazine, 2018) ...... 3

Figure 2- 1: Upgrading processes ...... 10

Figure 2- 2: Overview of Reactor Design for Aquaprocessing of Bitumen ...... 20

Figure 2- 3: Packed Bed Reactor ...... 26

Figure 3- 1: Boiling Point Distribution Curve from High Temperature Simulated Distillation ... 35

Figure 3- 2: Process and Instrument Diagram Reactivity Testing Unit # 3 (RTU#3) ...... 36

Figure 3- 3: Reactor Assembly, adapted from Thiago Righi (Righi, 2016) ...... 38

Figure 3- 4:Schematic representation of pre-treatment conditions ...... 41

Figure 3- 5:Schematic diagram summarizing the reaction start-up procedure ...... 43

Figure 4- 1: Product Distribution for Thermal Cracking ...... 63

Figure 4- 2: Performance of Aquaprocessing Catalysts - Total Acid Number (TAN) Reduction 66

Figure 4- 3: Performance of Aquaprocessing Catalysts - Viscosity Reduction ...... 67

Figure 4- 4: Performance of Aquaprocessing Catalyst-HDS ...... 69

Figure 4- 5: Performance of Aquaprocessing Catalyst–HCK* ...... 70

Figure 4- 6: Arrhenius Plots for Hydrocracking* (HCK*) Reaction in Aquaprocessing ...... 73

Figure 4- 7: Mass Transfer Limitations associated with Cat J17 ...... 75

Figure 4- 8: Variation in Mass Transfer Coefficient with Reaction Temperature ...... 78

Figure 4- 9: Diffusivity of Steam in Bitumen at Reactor Conditions ...... 79

Figure 4- 10: Reynolds Number vs. Schmidt Number ...... 81

List of Abbreviations

Abbreviation Description

ADU Atmospheric Distillation Unit

API American Petroleum Institute

ASTM American Society for Testing and Materials

Bbl. US Barrel of Oil bbl./d Barrels per day

C Carbon

CSC Catalytic Steam Cracking

DAO De-asphalted Oil

FBR Fixed Bed Reactor fgl Two-phase frictional factor

GC Gas Chromatograph

GDP Gross Domestic Product

GHGs Greenhouse Gases

H Hydrogen

HCK* Hydrocracking*

HDI Human Development Index

HDS Hydrodesulfurization

HTSD High temperature Simulated Distillation

IBP Initial Boiling Point

MB Mass Balance

xii

MFC Mass flow controller

N Nitrogen

O Oxygen

P Pump

PFR Plug Flow Reactor

PI Pressure Indicator

R Hydrocarbon

Reg Gas-phase Reynolds Number

Rel Liquid-phase Reynolds Number

S Sulfur

Sc Schmidt Number

SCO Synthetic Crude Oil

SDA Solvent De-Asphalting

SRU Solvent Recovery Unit

T Tank

TI Temperature Indicator

TIC Temperature Indicator along with Heating Tapes

V Valve

VDU Vacuum Distillation Unit

VGO Vacuum Gasoil

VR Vacuum Residue

WOR Water to Oil ratio

xiii

List of Symbols

Symbol Description Units

2 am External Surface Area of the Catalyst m /g

3 CA Concentration of Species A mol./dm

3 Cvr Concentration of Vacuum Residue mol./dm

gl Pressure-drop per unit Length of the Reactor psi/m dp Diameter of the Catalyst Particle mm dT Internal Reactor Diameter mm

2 DWB Diffusivity of Steam in Bitumen m /s

g Gas Holdup fraction of reactor volume

l Liquid Holdup fraction of reactor volume

Fvr Molar Flow rate of Vacuum Residue mol./s g Accerlation due to Gravity m/s2 k Reaction Rate Constant for PFR s-1 k' Reaction Rate Constant for PBR dm3/s/kg km Mass Transfer Coefficient cm/s

' 3 kr Surface Kinetic Rate Constant dm /s/kg r Reaction Rate for PFR mol./s/dm3 r' Reaction Rate for PBR mol./s/kg

Catalyst Bulk Density g/ml c

Gas-phase Density kg/m3 g

xiv

liquid phase density kg/m3 l

 Total Acid Number mgKOH/g ug Superfacial Gas Velocity m/s ul Superfacial Liquid Velocity m/s

V volume of the reactor dm3

V0 volumetric flow rate of oil ml/h

Vw volumetric flow rate of water ml/h

W Weight of the Catalyst g

WHSV Weight Hourly Space Velocity h-1

X conversion %

CHAPTER 1: Introduction

1.1 Introduction

The discovery of the fossil fuels such as coal, oil and natural gas marked the beginning of the industrial revolution. The rising industrialization results in economic growth, urbanization and increase in energy consumptions (Shahbaz & Lean, 2012). The Gross Domestic Product (GDP) and Human Development Index (HDI)are some of the few reliable methods to track the pace of the industrialization of a nation. P. Rez used GDP per capita vs. energy consumption per capita to compare different economies in the world and as illustrated in Figure 1-1. As expected, the developed countries lie under the highest energy consuming nations. This shows that the energy demand is proportional to economic and social development (Rez, 2017)(Huc, 2011). According to U.S. Energy Information Administration, the world energy demand will increase by 28% between 2015 and 2040 (U.S. Energy Information Administration, 2017).

Figure 1- 1: Energy per Capita vs. GDP per Capita (Rez, 2017) with permission

Energy will continue to shape the economies all around the world. (Guelph Municipal Holdings

Inc., 2017). The rapid growth in developing countries like India and China will continue to 1 increase the demand for energy (Feng, et al., 2010). Consequently, it will result in inflating greenhouse gas emissions. According to Article 2 of the Paris Agreement, the rise in global temperature is directly related to carbon dioxide emissions from burning fossil fuels (United

Nations, 2015). 195 countries signed this agreement with a commitment to limit the global average temperature to 2°C above the pre-industrial levels (Robinson & Shine, 2018). Most of these countries are committed to making financial investments to lower greenhouse gas emissions (GHGs)(United Nations, 2016). Renewable energy sources are envisioned as one of the potential alternative solutions to address the climate change (Baranes, et al., 2017). Although a lot of work is being done in the renewable energy sectors, the fossil fuels (gas, oil and coal) will continue to meet 80% of the world energy demand (Huc, 2011)(Miljkovic, et al., 2016).

Total demand for oil increased by 11 million bbl./d during 2006 - 2015 period and it is expected to grow at a similar rate for the next 30 years (U.S. Energy Information Administration, 2017).

With more than 10% of worldwide proven oil reserves (Table 1-1), Canada plays an important role in meeting these increasing demands. Currently, 4.6% of the world oil production is based in

Canada; particularly, most of the oil production (~97 %) being carried out in Alberta province.

As shown in Figure 1-2 approximately 86% of the oil produced in Alberta is either bitumen or heavy oil.

Table 1- 1: Petroleum Statistics of 20151(U.S. Energy Information Administration, 2017) Parameter World Canada Proved Oil Reserves 1697.6 172.2 (Thousand million barrels) Production 91670 4385 (Thousands of barrels per day) Consumption 95008 2322 (Thousands of Barrels per day)

1 The difference in the consumption and production data is because of consumption of non-petroleum additives, alternate fuels and disparities in measurements and conversion of oil supply and demand data. 2

110

380 Conventional Heavy 83 961 Conventional Light & Medium Condensate

Bitumen

Upgraded Bitumen 1842

Figure 1- 2:Alberta Oil Production (thousand bbl./day) (Oil Sands magazine, 2018)

The high content of asphaltene and heteroatoms such as sulfur and nitrogen, and metals like nickel and vanadium make the extraction and processing of heavy oils and bitumen highly energy demanding. These oils are blended with lighter hydrocarbons for pipeline transportation.

Furthermore, the conventional thermal upgrading processing, applied to these feedstocks, has a concomitant carbon rejection which increases the carbon footprint of these oils (Speight, 2006).

To address these increasing energy demands and meet the environmental constraints, the oil producers need to embrace more energy efficient pathways to produce and transport oil(Huc,

2011). Using less energy intense processes will not only help addressing the environmental crisis but also lowers the operational cost for the oil production and refining facilities.

1.2 Motivation and Objectives

The existing pipeline infrastructure has reached their maximum capacity. The provincial and federal governments are working with the pipeline companies to build more pipelines to ship

Alberta crude oil to North American and Asian markets (Fellows, et al., 2017). These efforts are

3 being continuously obstructed by different branches of environmental and governmental agencies for various reasons related to sustainable energy policies, long term environmental impacts and royalty distributions among the provisional governments. Currently, bitumen is blended with 30 - 40 vol.% diluent to meet the pipeline specifications. Many researchers are developing technologies to partially upgrade bitumen to minimize or eliminate these diluent requirements to increase the bitumen carrying capacity of the existing pipelines. Aquaprocessing is one of these partial upgrading processes, where the hydrogen produced via catalytic steam cracking reacts with thermally and/or catalytically cracked heavier hydrocarbon to form upgraded and lighter hydrocarbons(Pereira-Almao, et al., 2013).

Over the past decade under Dr. Pereira’s supervision, researchers have made great progress in process optimization and catalyst preparation (Pereira-Almao, et al., 2013). The research works done by various MSc. and PhD students under his supervision have successfully demonstrated the application of Aquaprocessing technology for reducing total acid number, viscosity and vacuum residue content in de-asphalted oil (DAO) and vacuum gasoil(VGO) (Trujillo-Ferrer,

2008) (Fathi & Pereira-Almao, 2013) (Carbognani-Arambarri, 2014) (Garcia-Hubner,

2015)(Bernal-Sardi, 2017).

The main focus of the work presented in this thesis is to demonstrate the use of Aquaprocessing technology for the field upgrading application and evaluate three key reactor design parameters: i) reaction kinetics, ii) mass transfer limitations and iii) hydrodynamic properties required for scale-up of this process. The following work was carried out to meet the main objectives:

I. Design and construct a lab scale pilot plant

II. Characterize catalyst materials and analyze the feed

III. Perform thermal upgrading of bitumen to establish the baseline for the catalytic reactions

IV. Characterize Synthetic Crude Oil (SCO) to calculate vacuum residue conversion, total

acid number reduction, viscosity reduction, sulfur removal and their stability

V. Calculate kinetic parameters for all the catalysts for vacuum residue hydrocracking

reaction

VI. Evaluate Schmidt number and Reynolds Number required for operating parameter

sensitivity analysis

VII. Evaluate hydrodynamic properties: a) flow regime b) pressure drop and c) gas and liquid

holdup for a Fixed Bed Reactor with cocurrent upflow of steam and bitumen.

1.3 Thesis Organization

This thesis is organized in five chapters. The first chapter provides the motivation and

objective of the research. Chapter 2describes the background information and key literature

review related to the current thesis work. Chapter 3covers the experimental methods utilized for

catalyst characterization and analyzing liquid hydrocarbons as well as process gases. In addition,

Chapter 3 includes the details of reactor assembly and pilot plant setup for Aquaprocessing of

bitumen. Chapter 4 includes discussion of the experimental results obtained using the methods

and set-up described in Chapter 3; and mass transfer limitation associated with the catalyst

particle size, diffusion of steam in bitumen, sensitivity parameters and hydrodynamic properties

are examined in last half of this chapter. The final chapter, Chapter 5,outlines the overall

summary of the present study and recommendations for future work to further improve the

findings of this thesis.

CHAPTER 2: Literature Review

This chapter aims to provide the background information required to understand the work presented in this thesis. The first section includes information about crude oils and their basic classifications. The second and third sections provide details about bitumen transportation and various upgrading techniques currently being used to improve the quality of the oil. The fourth section provides a summary on bitumen upgrading in Alberta; the concept of partial upgrading is discussed in the fifth section. Building on discussion on Aquaprocessing in the sixth section, the last section will introduce various parameters that needs to be evaluated for the design of the

Fixed Bed Reactor with cocurrent upflow of steam and bitumen.

2.1 Crude Oil

Different authors, institutes and companies have their own definition and classifications for the crude oil (Huc, 2011)(Speight, 2006). According to ASTM D4175, crude oil is defined as a naturally occurring hydrocarbon mixture, generally in liquid state, which may contain organic compounds having sulfur, nitrogen, oxygen, metals and other elements. Petroleum, crude petroleum and crude are commonly used as equivalent terms in the industry (ASTM

International, 2018). As listed in Table 2-1, crude oil is classified into light, medium and heavy depending on the oAPI gravity(Huc, 2011).

o 141.5 API gravity = − 131.5Equation 2- 1 푆퐺 where, SG is the specific gravity of the crude oil and is equal to the ratio of density of crude oil to density of water at 60 oF (15.56oC).

The heavy crude oil is further classified into Heavy oil, Extra-heavy oil and Natural bitumen based on its viscosity and mobility at reservoir conditions (Table 2-2).

Table 2- 1: Crude Oil Classification Based on API Gravity

Classification Specific Gravity oAPI Gravity

Light <0.87 >31.1

Medium Between 0.87 and 0.92 Between 22.3 and 31.1

Heavy >0.92 <22.3

Table 2- 2: Heavy Crude Oil Classification

Classification oAPI gravity Viscosity (cP) Mobility

Heavy >10 <10,000 yes

Extra-heavy <10 >10,000 some

Natural bitumen <10 >10,000 no

Canada has 171 billion barrels of proven oil reserves and about 97 % of it is located in Alberta.

Majority of Alberta’s heavy oil falls in the bitumen category. This heavy oil is produced by either open-pit mining or in-situ processes such as Steam assisted Gravity Drainage (Natural

Resources Canada, 2014). The oil from these production sites needs to be transported to the refineries which are located hundreds of miles away.

The increasing demand for Alberta Oil in countries like China is of great economic and political advantage for Canada as this opens the market for bitumen in countries other than the United

States. Access to this market is not possible without the construction of Enbridge Northern

Gateway pipeline. This pipeline will transport crude from Athabasca oil sands to marine terminal at the western coast of Vancouver to load it on the oil tankers and deliver to China (Banerjee,

2012) . Unfortunately, this project is getting delayed because of a series of political, economic

7 and environmental reviews it needs to go through. These reviews can take several years before any of the Alberta oil can be shipped to Asian countries (Bowles & MacPhail, 2017). As a result, all the bitumen produced in Alberta must be sold in North American market using existing infrastructure and Keystone and Trans Mountain pipelines upon their completion.

2.2 Bitumen Transportation

The remote location of the production sites makes the bitumen transportation one of the biggest challenge for the Alberta oil industry. More than 95 % of the bitumen is hauled to the refineries via pipelines and only 4 - 5 % is shipped using rail cars because of the inefficiency and safety concerns associated with their usage. To meet the pipeline specifications (Table 2-3), the heavy oil needs to be blended with diluents such as light crudes, condensates and naphtha to reduce its viscosity before shipping to refineries through pipelines (Banerjee, 2012) (Hassan, et al., 2010).

These diluents/solvents tend to increase the intermolecular distance between the oil molecules and results in reduction in viscosity and density. The choice of the diluent is governed by economics and availability in the field (Huc, 2011). In Alberta, Natural gas derived condensate is the preferred choice because of its availability.

Table 2- 3: Pipeline Specifications (Keeson & Gieseman, 2018)

Properties Specifications Athabasca Bitumen

Viscosity <350 cSt at pipeline temperature 5000 to 300,000 cSt at 25°C

Density, kg/m3 < 940 1015

°API Gravity, °API >19 7.9

Sediment and water content < 0.5 vol.% 0-2%

Olefin content < 1 wt.% 0

Chlorine, ppm <1 >25

The increasing bitumen demand along with opposition faced by the pipeline construction projects and the price differential between the bitumen and synthetic crude oil (SCO) make the upgrading of bitumen more attractive for the producers.

An economic analysis done by Davudov and Moghanloo showed that bitumen upgrading increases the net margin by US$ 6 to 8 per barrel (Davudov & Moghanloo, 2017). To unlock this margin, some producers ship the blended crude oil to the nearest upgrader to increase the content of the desirable products before shipping it to the refineries. At the upgrading facilities, the diluent is separated from the bitumen in a Solvent Recovery Unit (SRU) and is recycled back to the production sites. Crude oil is then distilled using Atmospheric Distillation Unit (ADU) and

Vacuum Distillation Unit (VDU). The bottoms from VDU called vacuum residue (VR) is then send to the upgrader for further processing using either carbon rejection or hydrogen addition upgrading processes.

2.3 Upgrading

“Upgrading” is defined as a process to improve the physical properties and chemical composition of the oil by carbon rejection or hydrogen addition. The upgraded products have higher API, lower viscosity, lower sulfur, nitrogen and asphaltene content than the bitumen. The upgrading processes can be subdivided into two main categories, Non-Catalytic Carbon

Rejection and Catalytic Hydrogen Addition. In both cases, the final upgraded product has lower carbon to hydrogen ratio than the original bitumen (Banerjee, 2012) (Huc, 2011). The list of these processes is presented in Figure 2-1.

Solvent Deasphalting Visbreaking Non-Catalytic Carbon Rejection Thermal Delayed Coking Cracking/Coking

FluidCoking/ Flexicoking

Upgrading Trickle Bed Reactor

Bubble Bed Reactor Catalytic Hydrocracking Hydrogen Addition Ebullated Bed Reactor

Slurry Bed Reactor

Figure 2- 1: Upgrading processes

2.3.1 Non-Catalytic Carbon Rejection

In the carbon rejection processes the goal is to remove heavy carbonaceous species via either

Solvent De-asphalting or Thermal Cracking (Speight, 2006). The brief overview of these processes is discussed below.

2.3.1.1 Solvent De-Asphalting (SDA)

SDA is a separation process in which paraffinic solvents such as propanes, butanes, pentanes, hexanes and heptanes are used to precipitate asphaltenes and heavier resins. The quality and quantity of asphalt and De-Asphalted Oil (DAO) can be optimized by changing the solvents, solvent to oil ratio and temperatures. Lower molecular weight solvents have less solvency power for the asphalt fraction, higher solvent to oil ratio will result in lower asphaltene precipitation; and temperature increase results in increase in the solvency power of the solvent. Other variables such as feed flow rate, operating pressure and solvent injection rate can also impact the

10 operations(Speight, 2006). KBR licensed Residuum Oil Supercritical Extraction Process (ROSE) is an example of SDA process. This process extracts DAO from atmospheric residue (AR) and/or vacuum residue (VR) using light hydrocarbon solvents. Majority of the solvent is recovered in downstream de-asphalted oil separator and this solvent recovery process is significantly improved with the addition of de-asphalted oil stripper and asphaltene stripper. DAO from ROSE unit can be used a lube-oil blending stock and feed for the fluid catalytic cracking (FCC) units to produce gasoline(KBR, Inc., 2013).

2.3.1.2 Thermal Cracking/Coking

Thermal cracking is another non-catalytic upgrading process in which the heaviest, hydrogen deficient fraction of the feed containing metals, sulfur and nitrogen is rejected as coke. The pyrolysis of heavier hydrocarbons at higher temperatures results in production of highly olefinic and sulfur rich aromatic products via free radical mechanisms. Three types of thermal cracking processes are used in the petroleum industry are Visbreaking, Delayed Coking and Fluid

Coking/Flexicoking are three main thermal cracking processes(Fahim, et al., 2009). These processes mostly have downstream hydrogenation units for olefin saturation as well as sulfur and nitrogen removal.

2.3.1.2.1 Visbreaking

Visbreaking is a non-catalytic process that lowers the viscosity of the residue fraction via pyrolysis of high molecular weight hydrocarbons into lighter fractions. This lowers the diluent requirement for meeting the viscosity constraints. Coil cracker and Soaker cracker are two types of commercially used visbreakers. The coil cracker operates at a higher temperature range (470-

500 °C) and lower residence time in order to meet the conversion targets whereas in the soaker cracker because of the addition of soaker drum downstream of the feed heater, similar

11 conversions can be achieved at a lower temperature range (430-450 °C) because of longer residence time(Speight, 2006). The product quality and yields can be optimized by changing the operating temperature and residence time while monitoring the product stability. The poor product stability would result in asphaltene precipitation and cause fouling in the heater coils, soaker drum and other downstream units. Shell Soaker Visbreaking process licensed by Shell and CB&I Lummus is widely used in the refineries to process atmospheric and vacuum residue.

The specialized internals of the soaker drum minimize the back-mixing allowing for achieving higher conversions without damaging the fuel oil stability.

2.3.1.2.2 Delayed Coking

Delayed Coking is a thermal cracking process in which the feed is heated slightly above the required reaction temperature of about 480 °C before it enters the coker drums where the pyrolysis of hydrocarbons occurs. The reaction products, olefins and aromatic liquids, require further hydrogenation while coke is rejected in the drums. Delayed Coking is a semi-continuous process as the coke drums need to be switched after 24-48 hours cycles(Fahim, et al., 2009)(Huc,

2011). The use of terrace-wall double-fire furnace and advanced coke drum design makes Amec

Foster Wheeler’s SYDECSM (Selective Yield Delayed Coking) a preferred choice for upgrading industry.

2.3.1.2.3 Fluid Coking and Flexicoking

Fluid Coking and Flexicoking are other two widely used technologies in the refining industry.

The Fluid coking process consists of a fluidized bed reactor and a fluidized bed burner. The typical operating temperature for the reactor and the burner are 510-566 °C and 593-677 °C, respectively. In this process, VR feed enters the scrubber where the fine coke particles are recovered before it enters the reactor through nozzles. The VR feed along with the steam keeps

12 the bed of coke particles fluidized. The gases and vapors pass through another scrubber to a distillation column for further separation. Some of the coke from the reactor flows into the burner where part of it is burned to supply heat(Fahim, et al., 2009).

Flexicoking is similar to Fluid Coking except a fluidized bed operating at 816-982 °C acts as a gasifier. Because of this modification, coke production in Flexi-coking is 90 % lower than Fluid

Coking process(Speight, 2006). An example is ExxonMobil licensed FLEXICOKINGTM.

2.3.2 Hydrogen Addition

As opposed to the Carbon rejection processes discussed earlier, in the following described processes, hydrogen is added to the oil in the presence of a catalyst. The free radicals formed via thermal and/or catalytic cracking of heavier hydrocarbon molecules react with hydrogen to form light fractions. The key difference in various hydrogen addition processes is the reactor type.

Four types of reactors used in petroleum industry are fixed bed, moving bed, ebullated bed and slurry bed. The extent of reaction and the product slate can be optimized by changing the reactor dimensions, reactor internals, operating conditions (temperature, pressure, Hydrogen to oil ratio) and catalyst selection.

2.3.2.1 Trickle Bed Reactor

Trickle bed reactors have fixed beds of catalyst with cocurrent downflow of gas and liquid. The term, trickle comes from the trickle flow pattern which exists at low liquid feed rates. The hydrodynamics and mass transfer inside these reactors are highly influenced by the flow rates and physical properties of the gas and liquid feed(Ramanchandran & Chaudhari, 1983).

Examples are: Continuous catalyst Replacement (CCR) by CLG, Hycon by Axen and Hyvahl by

Shell and Axen(Fahim, et al., 2009).

2.3.2.2 Fixed-Bed Reactor with Cocurrent Upflow

As the name suggest, in these reactors the liquid feed and the gas are fed from the bottom of the reactor and the gas is dispersed in continuous liquid phase. These reactors are also referred as packed bubble column reactors because the gas bubble flows unbroken in a continuous liquid phase. The upward flow of the liquid improves the wettability of the catalyst surface and as a result, more catalyst surface is available for the reaction to take place. These reactors exhibit better mass and heat transfer efficiencies than the trickle bed reactors. These reactors are commonly used in the laboratory pilot plants to test the catalyst activities and kinetic modeling

(Ramanchandran & Chaudhari, 1983). Example: UFR, Up-flow reactor by Shell(Fahim, et al.,

2009).

2.3.2.3 Ebullated Bed Reactor

In the ebullated bed reactor, the catalyst is fluidized by the upward flow of the gas and liquid reactants along with significant liquid recycle. This configuration allows for the continuous catalyst renewal therefore the turnaround time is independent of the catalyst deactivation. The ebullation allows for back-mixing and isothermal operations while eliminating the pressure build ups, bed plugging and channeling issues that can be experienced in the fixed bed reactors(Huc,

2011). H-OilRC licensed by Axens IFP Group Technologies and LC-Fining/LC-Max of Chevron

Lummus Global are two commercially used ebullated reactors in the upgrading industry(Fahim, et al., 2009).

2.3.2.4 Slurry Reactor

In these reactors the dispersed catalyst or catalyst precursors are injected continuously with the feed. The catalyst particles promote hydrogenation of the thermally cracked hydrocarbons and limits the coke formation. These reactors are designed for processing the heaviest vacuum

14 residue feeds which cannot be processed using fixed and ebullated bed reactors (Huc, 2011).

Example: Eni Slurry Technology, EST by Eni and Chevron Activated Slurry Hydroprocessing,

CASH by PDVSA-Intevep (Fahim, et al., 2009).

2.4 Upgrading in Alberta

Both thermal and catalytic upgrading processes are being used in Alberta’s oil industry. The demand for various products, volatility in the oil prices, price differential between light and heavy crudes and the labor constraints are the key driving parameters for the process selection(IHS, 2013). Before 2008’s global recession, five upgraders were under construction of which only three were completed while the other two were suspended or cancelled. Based on the process selection and design capacity, an upgrader construction can cost between $8 to $21B or more. All the upgraders in Alberta along with their processing capacity are listed below in Table

2-4.

Table 2- 4: List of Upgraders in Alberta

Project Name Technology Location Capacity (thousand bbl./d)

Athabasca Oil Sands Residue Fort Saskatchewan 269 Project -Scotford Hydroconversion

Suncor Base and Coking Fort McMurray 440 Millennium

Fluid coking and Syncrude Mildred Lake Fort McMurray 407 Hydrocracking

Canadian Natural Delayed coking and Fort McMurray 211 Resources Ltd Horizon hydrotreating

Nexen – Long Lake* Hydrocracker Long Lake 58.5*

*Nexen-Long Lake upgrader is not operational since 2016 (Dittrick, 2016) 15

2.5 Partial Upgrading

“Partial Upgrading” can be defined as a process to partially remove the contaminants and decrease the viscosity of the oil to reduce or eliminate the diluent addition to meet the pipeline specifications. The product properties are in the range of synthetic crude oil (SCO) and pipeline specifications. Although no commercial partial upgrading plants are operational at present but many technologies (Table 2-5) are being extensively explored in the pilot plant settings (Keeson

& Gieseman, 2018). Researchers have estimated that a 100,000 bbl./d capacity partial upgrader would cost only $3B which is significantly lower compared to a complete upgrading facility with similar capacity which may be around $13B (Oil Sands Magazine, 2015). The low initial investments and available government grants are likely to make these partial upgrading process an integral part of Alberta Oil industry (Coyne, 2018).

2.6 Aquaprocessing

Aquaprocessing is a partial upgrading process in which bitumen and steam are injected into a fixed bed catalytic reactor. The state of art bifunctional catalyst has two functionalities: catalytic steam cracking and hydrogenation. The hydrogen free radicals formed via steam cracking reaction at one active site reacts with hydrocarbon free radicals at the second active site to form lighter hydrocarbons (Perez Zurita, et al., 2015). This in-situ hydrogen generation from steam significantly lowers the upgrading cost by eliminating the need for a hydrogen production facility in the proximity of the unit. Depending on the catalyst and reaction conditions, the SCO has 80 – 98% reduction in viscosity, 80 – 100% reduction in total acid number, 10 – 20% sulfur removal and 10 – 34% reduction in the vacuum residue fraction. The simple design and mild operating conditions would result in lower investments and operating costs in comparison to other partial upgrading processes listed in Table 2-5.

Table 2- 5 : List of Partial-Upgrading Technologies

Partial Company Technology Claim Drawbacks in Reference Upgrading comparison to Technology Aquaprocessing Aquaprocessing PC-CUPS Catalytic steam cracking and 98% reduction in Work presented hydrogenation viscosity; in this thesis 40-60% reduction in diluent requirement to meet the pipeline specs JetShearTM Fractal Thermal cracking and jet nozzles 40-60% reduction in the Unit complexity and (Fractal Systems, Systems Inc. for cavitation and mechanical diluent addition for hydrogen addition for 2018) shearing pipeline specs meeting olefin spec HI-QR MEG Thermal cracking and solvent No diluent addition is Carbon footprint because (MEG Energy, Energy de-asphalting required of asphaltene removal 2015) VHTL Fluid Oil Thermal and mechanical 50% lower Investment Need hydrogen; coke (FluidOil, 2018) Ltd. cracking and hydrogenation cost and eliminates formation diluent requirements VCI ADC Value Asphaltene removal followed by Improved product Carbon rejection (Value Creation Creation Inc. thermal cracking quality Inc., 2016) SCW JGC Supercritical water cracking Improved Product 3200psi would require (Hisato Aoyama, Corporation quality special metallurgy 2014) DSU® Field Molten salt and hydrogenation Improved Product Hydrogen addition (Field Upgrading, Upgrading quality 2015) IYQ® ETX Plug-flow dryers and fluid Improved product Carbon rejection (ETXSYSTEMS Systems Inc. bedcoking quality IYQ Upgrading, 2017) UniflexTM UOP® Slurry hydrocracking Improved product Hydrogen addition (Haizmann, quality Robert and UOP LLC, 2011) EST® ENI Slurry hydrocracking Improved product Hydrogen addition (ENI, 2014) quality FTCrude® Expander Enhanced Fischer-Tropsch Increased yields Process complexity (Jan Wagner, Energy Steve Kresnyak, 2015)

2.6.1 Advances in Aquaprocessing

The Aquaconversion process was started in 1991 and two short term commercial runs were performed at PDVSA’s Isla refinery (Pereira-Almao, et al., 2001). The synthetic crude produced had 16°API gravity with 20% higher yields than delayed coking process. A study done by

PDVSA-Intevep and UOP LLC in 2001 showed that the commissioning of 100,000 bbl./d

Aquaconversion facility at wellhead will be economically competitive with diluent addition

(Pereira-Almao, et al., 2001). This project was never completed because of the lack of investments, corruptions and cash shortages (Delgado-Landaeta, 2015).

Over the last decade, Dr. Pereira and his research group have continued to improve over this process, developing novel catalysts and a process for partial field upgrading applications denoted as Aquaprocessing (AQP). This work have been captured in the theses of Gustavo Trujillo,

Andrew Carss, Lante Carbognani, Eduardo Garcia-Hubner, Thiago Righi, Fredy Navarro and

Lorena Bernal-Sardi (Trujillo-Ferrer, 2008) (Carss, 2014) (Righi, 2016)(Navarro, 2016) (Bernal-

Sardi, 2017). The work of the first two authors was primarily focused on use of unsupported ultra-dispersed catalyst for converting 350°C+ fraction in vacuum gasoil fraction and de- asphalted oils. All the later workson catalysts evaluations were carried out in a fixed bed reactor for the ease of operation and test the feasibility for processing the wider range of oil fractions.

During this period various catalysts have been studied to improve specific properties of the SCO produced via this process. Bernal-Sardi reported 44wt.% conversion of vacuum residue fraction for de-asphalted oil using nickel-cerium hydrotalcite with 10wt.% of molybdenum carbide catalyst.

Now, the need is to design a pilot plant with 1-100bbl./d capacity before deploying this technology for commercial field upgrading applications. Like any other catalytic upgrading

18 process, the catalyst and the reactor are the most critical component of this technology and the work presented in this thesis is a step towards that direction by evaluating some of the reactor design parameters.

2.7 Fixed-Bed Reactor with Cocurrent Upflow

Reactor design is a complex topic and requires a thorough understanding of reaction mechanisms, target conversions, reaction kinetics, fluid dynamics, heat and mass transfer(Rose,

1981). For the Aquaprocessing technology, a Packed Bed Reactor (PBR) with cocurrent upflow of feed and steam is being considered because it provides better catalyst wettability and mass & heat transfer efficiencies than downflow reactors. These upflow PBR are also referred as bubble column reactors because of the existence of bubble flow regime inside the reactor(Ramanchandran & Chaudhari, 1983). Shell licensed Up-Flow Reactor (UFR) for hydroprocessing feeds with high sulfur and metal contents is a commercial application of such reactors in the petroleum industry(Fahim, et al., 2009). These reactors are typically operated at low liquid and gas velocities such that the liquid phase is continuous phase and gas phase is the dispersed phase. The overview of the reactor design for Aquaprocessing of bitumen is shown in

Figure 2.2.

Figure 2- 2: Overview of Reactor Design for Aquaprocessing of Bitumen

2.7.1 Process Chemistry

To understand the reaction mechanism for the Aquaprocessing reaction it is important to look at two key reaction mechanisms, thermal cracking and steam reforming. Thermal upgrading processes are based on application of heat to break the C-C bonds of the heavier hydrocarbons to form light hydrocarbons. This reaction involves three steps: Chain initiation, Chain propagation and Chain termination.

1. In the chain initiation step, the cracking of the C-C bonds of molecules results in formation

of free radicals.

∎ ∎ 푅1 − 푅2 + ℎ푒푎푡 → 푅1 + 푅2 Equation 2- 2

2. In the chain propagation step, the free radicals formed in chain initiation step react with

different hydrocarbon molecules to form new hydrocarbon radicals. This step includes

hydrogen subtraction, addition, radical decomposition or isomerization. The chain

propagation step needs to be faster than initiation and termination steps for the formation of

lighter hydrocarbons.

∎ ∎ 푅3 + 푅1 → 푅3 + 푅1퐻 Equation 2- 3 ∎ ∎ And/or 푅1 → 푅4 + 푅5퐻 Equation 2- 4

3. The final chain termination step, two free radicals binds together to form stable

hydrocarbons. This reaction could result in products heavier than the molecules present in the

feed.

∎ ∎ 푅2 + 푅4 → 푅2 − 푅4 Equation 2- 5 ∎ ∎ 푅2 + 푅4 → 푅2 + 푅4퐻 Equation 2- 6 ∎ ∎ 푅1 + 푅2 → 푅1 − 푅2 Equation 2- 7

where, R and H are hydrocarbon molecules and hydrogen atoms, respectively, and subscript

1,2,3,4 and 5 are used to represent different hydrocarbon molecules. The superscript, ∎, is used to indicate the free radicals.

Steam has been extensively used as heat transfer media in oil extraction and to reduce coke formation in various upgrading processes (Chen & Scott, 1987). In addition, steam-hydrocarbon reforming to produce hydrogen has been around for almost a hundred years. In the steam reforming process, the water molecules react with hydrocarbons in the presence of catalyst to produce hydrogen. The process is based on catalytic steam cracking and thermal cracking mechanisms. In this process, both total and selective steam reforming are possible. In total steam reforming, the hydrocarbon molecules react with steam and produce hydrogen while in selective steam reforming C-C bond of alkyl-aromatics is targeted. This selective steam reforming reaction can be viewed as steam dealkylation (SDA) (Perez Zurita, et al.,

2015)(Trujillo-Ferrer, 2008).

Total catalytic steam reforming is generally carried out on light hydrocarbons such as methane or naphtha.

퐶푛퐻푚 + 2푛퐻2푂 푛퐶푂2 + (2푛 + 푚/2) 퐻2 Equation 2- 8

As described earlier the selective steam reforming takes place in alkyl-aromatics. For example, in case of toluene the reaction targets C-C bond between the methyl and benzene ring.

퐶푛퐻푚 + 퐻2푂 퐶푥퐻푦 + 푔푎푠 (퐻2, 퐶푂2) 푥 < 푛 Equation 2- 9

In Aquaprocessing,both thermal cracking and steam cracking reactions happen simultaneously.

Pereira-Almao et. al(Pereira Almao, et al., 2013)proposed a reaction mechanism where hydrogen produced via catalytic dissociation of water molecules and it is used for free radical saturation.

The hydroxyl free radicals react with hydrocarbon free radicals in the chain propagation step.

Other feasible reactions happening during Aquaprocessing are hydrocarbon steam reforming, steam cracking, partial steam cracking, incomplete partial steam cracking, thermal

22 dehydrogenation, catalytic hydrogenation and steam decarboxylation. The reaction mechanisms for these reactions are listed in Table 2-6.

Table 2- 6: Reactions Occurring During Aquaprocessing of Bitumen Reaction Proposed mechanism

푅 − 푅 + ℎ푒푎푡 → 푅 ∎ + 푅 ∎ 1 2 1 2 Equation 2- 10 Thermal Cracking

퐻 푂 → 퐻∎ + 푂퐻∎ Water Catalytic 2 Equation 2- 11

Dissociation 푅 ∎ + 푅 ∎ + 2퐻∎ → 푅 퐻 + 푅 퐻 Free radical 1 2 1 2 Equation 2- 12 saturation 푅 ∎ + 2푂퐻∎ → 푅 + 퐶푂 + 퐻 1 6 2 2 Equation 2- 13 Oxidation

∎ ∎ Equation 2- 14 푅2 + 푅4 → 푅2 − 푅4 Free radical ∎ ∎ Equation 2- 15 polymerization 푅2 + 푅4 → 푅2 + 푅4퐻 (condensation) ∎ ∎ Equation 2- 16 푅1 + 푅2 → 푅1 − 푅2 Hydrocarbon 푥 퐶 퐻 + 2푛퐻 푂 → 푛퐶푂 + (2푛 + ) 퐻 Equation 2- 17 Steam reforming 푛 푥 2 2 2 2

Steam Cracking 퐶푛퐻푥 − 퐶퐻2 − 퐶푚퐻푦 + 2퐻2푂 → 퐶푛퐻푥+1 + 퐶푚퐻푦+1 + 퐶푂2 + 2퐻2 Equation 2- 18

Partial Steam 퐶 퐻 − 퐶퐻 + 2퐻 푂 → 퐶 퐻 + 퐶푂 + 3퐻 Equation 2- 19 Cracking 푛 푥 3 2 푛 푥+1 2 2 Incomplete Partial 퐶 퐻 − 퐶퐻 + 퐻 푂 → 퐶 퐻 + 퐶푂 + 2퐻 Equation 2- 20 Steam Cracking 푛 푥 3 2 푛 푥+1 2 Thermal 퐶 퐻 − 퐶퐻 − 퐶퐻 − 퐶 퐻 → 퐶 퐻 − 퐶퐻 = 퐶퐻 − 퐶 퐻 + 퐻 Equation 2- 21 Dehydrogenation 푛 푥 2 2 푚 푦 푛 푥 푚 푦 2 Catalytic 퐶 퐻 − 퐶퐻 = 퐶퐻 − 퐶 퐻 + 퐻 → 퐶 퐻 − 퐶퐻 − 퐶퐻 − 퐶 퐻 Equation 2- 22 Hydrogenation 푛 푥 푚 푦 2 푛 푥 2 2 푚 푦 Acid Steam 퐶 퐻 − 퐶퐻 − 퐶푂푂퐻 + 2퐻 푂 → 퐶 퐻 + 2퐶푂 + 3퐻 Equation 2- 23 decarboxylation 푛 푥 2 2 푛 푥+1 2 2

The species involved in the condensation step may or may not be the same that are produced in the thermal cracking step. The proposed mechanism was validated in the work of Eduardo

18 Garcia and Mazin Fathi (Fathi & Pereira-Almao, 2013) by using isotopic water (H2O ). The

16 16 16 18 18 18 authors have detected three different CO2 species ( O=C= O, O=C= O and O=C= O) using mass spectrometry of gaseous products(Garcia-Hubner, 2015).

2.7.2 Process Conditions

The operating parameters such as temperature, pressure, Weight Hourly Space Velocity (WHSV) and water to oil ratio(WOR) have significant impact on the reaction kinetics. Consequently, these parameters need to be optimized in series of pilot plant experiments. The best operating conditions found by Eduardo Garcia-Hubner, Thiago Righi, Fredy Navarro and Lorena Bernal-

Sardi (Garcia-Hubner, 2015) (Righi, 2016) (Navarro, 2016) (Bernal-Sardi, 2017) listed in the

Table 2-7 below were used for carrying out the work presented in this thesis.

Table 2- 7: Optimized Operating Conditions Parameter Optimal Range

Reaction Temperature (°C) 350-390

Operating Pressure (psig) 400

Weight Hourly Space Velocity (h-1) 0.25

Water to Oil Ratio (m/m) 5:100

2.7.3 Steps in Catalytic Reaction

As explained in Elements of Chemical Engineering Reaction Engineering textbook, a process involving porous catalyst particles can be broken down into seven steps including diffusion, adsorption, surface reaction and desorption (Fogler, 1999).

1) Diffusion of the reactants from the bulk fluid to the external surface of the catalyst

particle

2) Diffusion of the reactants from the surface to the internal catalytic surface through the

pores

3) Reactant adsorption on active sites present on the catalyst surface

4) Chemical reaction

5) Desorption of the products from the catalyst surface

6) Diffusion of the products from the inside of the catalyst particle to the outer surface

through the pores

7) Diffusion of the products from the external surface to the bulk fluid

The slowest step in this mechanism would determine the overall rate of reaction. For a kinetically controlled reaction the diffusion steps (1, 2, 6 and 7) needs to be faster than the reaction steps (3, 4 and 5). Otherwise, the diffusion would affect the reaction rate as the reactants will not be able to reach the active sites inside the pores. This diffusion could either be the external, diffusion of gases or liquids from the bulk flow to catalyst surface, or internal, diffusion inside the catalyst pores (Fogler, 1999). The particle size can play a significant role in diffusion of reacting species. In the diffusion-controlled reactions the use of smaller catalyst particles can increase the rate of reaction.

2.7.4 Packed Bed Reactor Design Equation

The amount of catalyst required to achieve the desired conversion of vacuum residue fraction can be calculated using packed bed reactor (PBR) design equation by assuming plug flow inside the reactor, i.e., the concentration varies only in the axial direction. As illustrated in Figure 2-3, a small section inside the reactor from containing small amount of catalyst (W) is considered to perform a molar balance for vacuum residue (VR) fraction. Before that, it is important to understand a key difference between the rate of reaction in plug flow reactor (PFR) and PBR.

Rate of reaction for a PFR (rA) is defined as number of moles of a species, A reacting per unit time per unit volume of the reactor(Fogler, 1999). For a given reaction, A  B and assuming the rate of reaction is first order with respect to concentration of A (CA), the rate law can be written as

푚표푙푒푠 푚표푙푒푠 −푟 ( ) = 푘퐶 ( ) Equation 2- 24 퐴 푠×푑푚3 퐴 푑푚3

The units of rate constant(k) are per unit time (s-1).

′ Rate of reaction for a PBR (푟퐴) is defined as number of moles of a species, A reacting per unit time per unit mass of the catalyst (Fogler, 1999). For a given reaction, A  B and assuming the rate of reaction is first order with respect to concentration of A(CA), the rate law can be written as

푚표푙푒푠 푚표푙푒푠 −푟′ ( ) = 푘′퐶 ( ) Equation 2- 25 퐴 푠×푘푔 퐴 푑푚3

The units for rate constant(푘′) arevolume per unit time per unit mass of the catalyst (dm3s-1kg-1).

If the PFR is packed with the catalyst, the amount of the catalyst (W, in kg) that can be loaded in

3 the given volume of the reactor(V, in dm ) would depend on the catalyst bulk density (휌푐, in kg/dm3 or g/cm3).Therefore, reaction rate constantcalculated for PFR (k) can be expressed as

′ product of reaction rateconstant for PBR (푘 ) and the bulk density of the catalyst (휌푐).

GenVR FVR, In

Figure 2- 3: Packed Bed Reactor

Using conservation of mass equation

푀표푙푎푟 푓푙표푤푟푎푡푒 표푓 푉푅 퐼푛 − 푀표푙푎푟 푓푙표푤푟푎푡푒 표푓 푉푅 푂푢푡 + 퐺푒푛푒푟푎푡𝑖표푛 = 퐴푐푐푢푚푢푙푎푡𝑖표푛

푊+∆푊 푑푁 푚표푙푒푠 푚표푙푒푠 ′ 푉푅 푚표푙푒푠 퐹푉푅 @ 푊( ⁄ℎ) − 퐹푉푅 @ 푊+ ∆푊 ( ⁄ℎ) + ∫ 푟푉푅푑푊 = ( ⁄ℎ) 푊 푑푡 Equation 2- 26

For Steady State condition

푑푁 퐴푐푐푢푚푢푙푎푡𝑖표푛, 푉푅 = 0 Equation 2- 27 푑푡

Therefore, Equation 2-26 can be reduced to

푊+∆푊 퐺푒푛푒푟푎푡𝑖표푛, 푟′ 푑푊 = 퐹 − 퐹 Equation 2- 28 ∫푊 푉푅 푉푅 @ 푊+∆푊 푉푅 @ 푊

The catalyst inside the reactor is divided into several sample subsections such that the rate of reaction is uniform for∆푾.

푊+∆푊 퐺푒푛푒푟푎푡𝑖표푛, 푟′ 푑푊 = 푟′ ∆푊 Equation 2- 29 ∫푊 푉푅 푉푅

SubstitutingEquation 2-29 inEquation2-28

′ 퐹푉푅 @ 푊+∆푊 − 퐹푉푅 @ 푊 = 푟푉푅∆푊

퐹 −퐹 푉푅 @ 푊+∆푊 푉푅 @ 푊 = 푟′ Equation 2- 30 ∆푊 푉푅

Taking the limit as ∆W approaches zero,

퐹푉푅 @ 푊+∆푊 − 퐹푉푅 @ 푊 ′ lim [ ] = 푟푉푅 ∆푊→0 ∆푊

푑퐹 푟′ = 푉푅 Equation 2- 31 푉푅 푑푊

The hydrocracking reaction for vacuum residue, VR follows first order reaction

3 kinetics(Carbognani-Arambarri, 2014). IfCVR(moles/dm ) is the concentration of species VR in

′ ′ the feed, the rate of reaction(푟푉푅) can be expressed as product of kinetic rate constant, 푘 and CVR 27

′ ′ − 푟푉푅 = 푘 ∗ 퐶푉푅 Equation 2- 32

Multiplying Equation 2-31 by -1 and compare it with Equation 2-32

푑퐹 푉푅 = −푘′ ∗ 퐶 Equation 2- 33 푑푊 푉푅

Molar flow rate of VR, FVR(moles of VR/h) can be written as product of the volumetric flow rate,

(ml/h),and the concentration of VR inside the reactor. In a plug flow reactor, the volumetric flow rate () is uniform throughout the length of the reactor and is equal to the inlet volumetric flow rate, 0(ml/h).

3 푚표푙푒푠 푑푚 ⁄ 푚표푙푒푠 퐹푉푅( ⁄ℎ) = 푣0 ( ℎ) ∗ 퐶푉푅 ( ⁄푑푚3) Equation 2- 34

Substituting Equation 2-34 in Equation 2-33 and assuming the kinetic rate constant is same throughout the reactor

푣 푑퐶 0 푉푅 = −푘′ ∗ 퐶 푑푊 푉푅

푊 푣0 퐶푉푅 1 ∫ 푑푊 = − ′ ∫ 푑퐶푉푅 0 푘 퐶푉푅,𝑖푛 퐶푉푅

푣 퐶푉푅,푖푛 푑퐶 푊 = 0 ∫ 푉푅 푘′ 퐶 퐶푉푅 푉푅

푣0 퐶푉푅,푖푛 푊 = ′ 푙푛 Equation 2- 35 푘 퐶푉푅

Concentration of vacuum residue (CVR) is changing along the length of the reactor. For the exit stream CVR can be defined as function of conversion, X:

퐶 − 퐶 푋 = 푉푅,𝑖푛 푉푅 퐶푉푅,𝑖푛

퐶푉푅 = 퐶푉푅,𝑖푛 (1 − 푋) Equation 2- 36

SubstitutingEquation 2-36 in Equation 2-35,

푣0 퐶푉푅,𝑖푛 푊 = ′ ln 푘 퐶푉푅,𝑖푛(1 − 푋)

푣 1 푊 = 0 푙푛 Equation 2- 37 푘′ (1−푋) The amount of the catalyst, W required for achieving desired conversion, X at a given feed flow rate, v0can be calculated using Equation 2-37 if kinetic rate constant, k’ is known. This equation can be further modified using Weight Hourly Space Velocity (WHSV)and the feed density (휌0) at delivery temperatureto derive an expression for k’.

푀푎푠푠 푓푙표푤 푟푎푡푒 표푓 퐹푒푒푑, 푚 (푘푔⁄ℎ) 푊퐻푆푉(ℎ−1) = 표 푊푒𝑖푔ℎ푡 표푓 푡ℎ푒 퐶푎푡푎푙푦푠푡 𝑖푛 푡ℎ푒 푟푒푎푐푡표푟, 푊 (푘푔)

푚0 푊퐻푆푉∗푊 푣0 = = Equation 2- 38 휌0 휌0

Substituting 푣0 from Equation 2-38 in Equation 2-37

푊퐻푆푉 1 퐾𝑖푛푒푡𝑖푐 푟푎푡푒 푐표푛푠푡푎푛푡, 푘′ = ∗ 푙푛 Equation 2- 39 휌0 (1−푋) kinetic rate constant, 풌′depends on feed composition, reaction temperature, catalyst composition, age of the catalyst, catalyst deactivation etc., so it needs to be evaluated if any of these variable changes.

2.7.5 Mass Transfer

Diffusion is the movement or mixing of the molecules and atoms because of random thermal motion. In the absence of other gradients such as temperature and pressure, diffusion happens from region of higher concentration to lower concentration. The kinetic rate constant, 푘′ obtained using design equation for packed bed reactor consists of two parts: modified external

′ ′ mass transfer coefficient, 푘푚 and true kinetic rate constant, 푘푟. The latter accounts only for the

29 surface reaction whereas the former accounts for the diffusion limitations that can potentially impact the reaction rate(Smith, 1970).

1 1 1 ′ ′ = ′ + ′ ; 푘푚 = 푘푚푎푚 Equation 2- 40 푘 푘푚 푘푟 where, km is modified mass transfer co-efficient and am is the external surface area per unit mass

′ ′ of the catalyst, respectively. If the reaction rate constant 푘푟 is very large compare to 푘푚 then

′ mass diffusion will control the overall kinetics and a large 푘푚 means overall reaction rate is surface reaction controlled.

Intrinsic mass transfer also known as Knudsen diffusion can be avoided by using the catalyst with pore diameter larger than the mean free path of the molecules (Fogler, 1999).

2.7.6 Flow regime

Many researchers have studied the fluid hydrodynamics, gas and liquid holdups and pressure drop for a fixed bed reactor with cocurrent upflow of liquid and gaseous reactant. Eisenklam and

Ford identified two type of flow regimes by changing the gas feed rate. Their work showed a single-phase pore flow at low gas rates and two-phase at high gas flow rates (Eisenklam & Ford,

1962).Turpin and Huntington in 1967 proposed three distinct flow regimes: a) spray flow b) bubble flow and c) slug flow(Turpin & Huntington, 1967). Spray flow occurs at low liquid to gas flow rates, bubble when gas bubbles flow unbroken through the continuous liquid phase and slug flow when the alternate more or less dense phases pass through the column. Saada (Saada,

1972)developed an equation to evaluate minimum Reynolds numbersfor gas phase to ensure two-phase flow.

0.38 2 푑푝 푅푒퐺,푚𝑖푛 = 0.44 푅푒퐿 ( ) Equation 2- 41 푑푇

30 where,푅푒퐺,푚𝑖푛is the minimum gas phase Reynolds number required for two-phase flow, 푅푒퐿is the liquid phase Reynolds number, 푑푝is the diameter of the catalyst particle and dTis the reactor diameter, respectively.

Fukushima and Kusaka added the transition regions to Turpin and Huntington classifications and developed the equations in terms of ReG, ReLand (dp/dT) to identify these flow regimes(Fukushima & Kusaka, 1979). These equations are listed below in Table 2-8.

Table 2- 8: Fukushima and Kusaka's Flow Regimes Equations

Boundary Equation

Bubble (I)-churn 푑 −2.5 Equation 2- 42 푅푒 ( 푝) = 1.9 푋 10−4 퐺 푑 푇 Bubble (I)-pseudo-spray 푑 −3.1 Equation 2- 43 푅푒 푅푒1.8 ( 푝) = 2.0 푋 108 퐿 퐺 푑 푇 Churn-pseudo-spray 푑 −0.9 Equation 2- 44 푅푒 푅푒0.9 ( 푝) = 2.3 푋 104 퐿 퐺 푑 푇 Bubble (I)-bubble (II) 푑 −0.64 Equation 2- 45 푅푒 푅푒0.24 ( 푝) = 7.6 푋 102 퐿 퐺 푑 푇 Bubble (II)-pseudo-pulse 푑 −4.0 Equation 2- 46 푅푒 ( 푝) = 4.5 푋 105 퐺 푑 푇 Pseudo-spray-pseudo-pulse 푑 −1.7 Equation 2- 47 푅푒 ( 푝) = 2.8 푋 103 퐿 푑 푇 Pseudo-pulse-pulse 푑 −5.5 Equation 2- 48 푅푒 ( 푝) = 4.8 푋 107 퐺 푑 푇 Pseudo-spray-pulse 푑 −4.5 Equation 2- 49 푅푒 푅푒0.5 ( 푝) = 2.0 푋 107 퐿 퐺 푑 푇

2.7.7 Pressure Drop

Pressure drop also known as pressure differential across the reactor is one of the key operating parameter for a hydrocracking reactor. It can influence the reactor efficiency as high pressure build up can affect the flowrates and temperature gradient across the reactor. The main cause of

31 pressure build ups are bed packing, catalyst attrition and coke deposition. The latter two can be addressed by optimizing the catalyst design and reaction conditions while the former needs to be addressed at the design stage by specifying the maximum flow rates and effective diameter of the catalyst particle for a given reactor. The lab pilot plant tests may not produce reliable data for predicting the pressure drop for a scale-up reactor, so it needs to be estimated using most suitable empirical correlations. To predict the pressure-drop for the Aquaprocessing reactor some of the equations developed by various authors mentioned in above section will be used. These correlations tend to give similar results except at lower liquid to gas flow ratios(Ramanchandran

& Chaudhari, 1983).

Turpin and Huntington (Turpin & Huntington, 1967)used the friction factor approach

2 2푓푔푙푢푔휌퐺 훿푔푙 = Equation 2- 50 푑푝푒

2 3 푙푛푓푔푙 = 8 − 1.12 ln 푍 − 0.0769 (ln 푍) + 0.012 (푙푛 푍)

1.167 1.518 푅푒퐺 퐷푃 0.3 ≤ 푍 < 500 where,푍 = 0.767 ( ) 푅푒퐿 퐷푇 where, 훿푔푙 is the pressure drop/unit length of the reactor, 푓푔퐿 is the two-phase friction factor, 휌퐺 is the gas phase density, 푢푔 is the superficial gas velocity, 푑푝푒 is the effective particle diameter and ReGand ReL are gas and liquid phase Reynolds number respectively.Saada developed such pressure-drop equations for the single-phase and two-phase flow regimes(Saada, 1972).

Table 2- 9: Saada's Pressure Drop Equations

Flow Regime Equation Single phase pore flow −1.1 Equation 2- 51 1 0.39 0.6 푑푝 ( ) 훿푔푙 = 0.024 푅푒퐺 푅푒퐿 ( ) 푔휌퐿 푑푇 Two phase pore flow −1.15 Equation 2- 52 1 0.51 0.35 푑푝 ( ) 훿푔푙 = 0.027 푅푒퐺 푅푒퐿 ( ) 푔휌퐿 푑푇

32 where, 훿푔푙 is the pressure drop/unit length of the reactor, 휌퐿 is the liquid phase density, g is the acceleration due to gravity, ReGand ReL are gas and liquid phase Reynolds number respectively and dp/dT is the ratio of catalyst particle diameter and internal reactor diameter.

2.7.8 Gas and Liquid Holdup

Gas and Liquid holdup are other significant parametersfor the determining the reactor efficiency.

The gas holdup lowers the volume of the reactor available for liquid phase hydrocracking reaction(Ramanchandran & Chaudhari, 1983). For this reason, the liquid hourly space velocity,

LHSV for the industrial reactors need to be adjusted accordingly to obtain conversions similar to those observed during the pilot test programs. Liquid holdup for the bubble regime can be estimated using empirical correlations developed by different researchers listed in Table 2-10.

휖푔 + 휀푙 = 휖퐵 Equation 2- 53

Table 2- 10: Liquid Holdups in a Packed Bed Reactor with Cocurrent Upflow

References Equation

휀 푅푒 0.25 Equation 2- 54 a) For single-phase pore flow 푙 = 0.48 ( 퐿 ) 휖퐵 푅푒퐺 (Saada, 1972) Equation 2- 55 휀 푅푒 0.07 b) For two-phase pore flow 푙 = 0.32 ( 퐿 ) 휖퐵 푅푒퐺

(Turpin & 0.24 0.24 휀 푢 휌 푢 휌 Huntington, 푙 = −0.035 + 0.182 ( 푙 퐿 ) for 1 ≤ ( 푙 퐿 ) ≥ 6 Equation 2- 56 1967) 휖퐵 푢푔휌퐺 푢푔휌퐺

휀푙 0.03 −0.28 0.5 Equation 2- 57 = 1.8푅푒퐿 푅푒퐺 푓표푟 푅푒퐿푅푒퐺 < 695 휖퐵 (Fukushima & 휀 Kusaka, 1979) 푙 0.17 −0.21 0.5 Equation 2- 58 = 0.72푅푒퐿 푅푒퐺 푓표푟 푅푒퐿푅푒퐺 > 695 휖퐵 where, 휖푔, 휀푙, and 휖퐵 are the gas, liquid and bulk holdup for the reactor, respectively; ReGand ReL are gas and liquid phase Reynolds numbers;푢푔 and푢퐿are the superficial gas and liquid velocities; and휌퐺and 휌퐿 are the gas and liquid phase densities; respectively.

Chapter 3: Experimental Section

This chapter outlines detailed description of the feedstock, pilot plant design and pilot plant experiments carried out to understand the impact of catalyst particle size on reaction kinetics and generate data to evaluate reactor design parameters as discussed in Section 2.7 of Chapter 2. The characterization of the Athabasca Bitumen is presented in the first section. The description of the pilot plant set-up and experimental procedure are given in the second and third section, respectively. The methodologies used to test the products (SCO and process gases) and the catalysts characterization are included in the fourth and fifth section, respectively.

3.1 Bitumen Feedstock

Athabasca Bitumen provided by Japan Canada Oil Sand Limited (JACOS) produced via Steam-

Assisted Gravity Drainage was used for pilot experiments for demonstrating the feasibility of using Aquaprocessing for partial upgrading and obtain data required for evaluating kinetic parameters as well as associated hydrodynamic properties. The feedstock was tested as reference for all the analytical experiments during the product characterization. The key properties are listed below in Table 3-1 and the boiling point curve obtained using high temperature simulated distillation is shown in Figure 3-1.

Table 3-1: JACOS Feedstock Properties

Properties Measured Values Properties Measured Values

Density (kg/m3) 1002.1 Hydrogen, H (wt.%) 10.5

API gravity (°API) 9.3 Sulfur, S (wt.%) 4.11

Dynamic Viscosity at 67728 Nitrogen, N (wt.%) 0.39 25°C (cP) Total acid number, TAN 2.34 *Oxygen, O (wt.%) 1.89 (mgKOH/g) Carbon, C (wt.%) 83.12 Vacuum Residue 50.57 (550°C+) (wt.%) *calculated by difference from C, H, S and N content

Boiling Point Distribution Curve for Jacos Bitumen 800

700

600 C) ° 500

400

300 Temperature Temperature ( 200 IBP= 170°C 100

0 0 20 40 60 80 100 Mass Fraction Distilled (wt%)

Figure 3- 1: Boiling Point Distribution Curve from High Temperature Simulated Distillation 3.2 Pilot Plant Setup

A new lab scale pilot plant called Reactivity Testing Unit # 3 was built in CCIT-062 at the

University of Calgary. The unit was designed to evaluate small amounts of catalysts (10 – 50g) in a fixed bed reactor with cocurrent upflow of bitumen and steam which can be operated at 0 –

500 psig pressure. The upper temperature limit must be restricted to 450 °C in the reactor to avoid plugging due to coke formation. The present work was carried out at temperatures between

350 °C and 390 °C with a pressure of 400 psig. LabVIEW program was used to control the operating conditions such as temperatures and flowrates.

The Process and Instrument Diagram (P&ID) is shown in Figure 3-2. The unit can be divided into three sections namely: feed section, reaction section and separation section.

Figure 3- 2: Process and Instrument Diagram Reactivity Testing Unit # 3 (RTU#3) 36

3.2.1 Feed Section

The feed section is designed to carry reactants such as bitumen, base oils, vacuum residue, water and hydrogen gas to the reaction section. It consists of two feed storage tanks, T-101 and T-102; three Teledyne Isco D-Series Syringe pumps, P-101, P-102 and P-103; two Brooks mass flow controllers, MFC-101 and MFC-102 and a steam generator.

Tank, T-102 is filled with JACOS bitumen while T-101 is filled with medium vacuum gasoil

(MVGO) or toluene. The feed from T-101 can be used to purge the unit if there is a need to switch the feed. Pumps (P-101 and P-102) are operated alternatively, i.e., one pump is filled with the feed while other supplies feed to the unit. Pump (P-103) is used to feed water which is heated to 100 °C before it enters the steamer. The steamer is a glass beads filled with 4” long and 3/8” diameter SS316 tubing and it operated at 300 °C to ensure uniform steam generation. This steam mixes with the bitumen at desired water to bitumen ratio before entering the reactor. All the equipment and associated lines are heat traced using heating tapes and temperature controlling thermocouples (TICs). The desired temperatures are set and monitored using LabVIEW program. Hydrogen and nitrogen flows are controlled by setting the percent opening of the aperture at LabVIEW for MFC-101 and MFC-102, respectively.

A spring-loaded pressure relief valve RV-102 is insulated on the main feed line as a safety guard.

It will open if the pressure in the main feed line goes above 700 psig and the effluents will get collected in the drain tank. The check valves are installed at various locations throughout the feed section to stop backflow of the liquids.

3.2.2 Reaction Section

The reaction section consists of a reactor, an internal thermocouple with 5 sensing points and temperature and pressure indicators before and after the reactor. The reactor diameter and length can be varied depending upon the amount of catalyst to be loaded and catalyst’s bulk density.

The present work was carried out using 30 cm (12”) long SS316 tube with 1.27 cm (0.5”) outer diameter and 0.089 cm (0.035”) wall thickness. The isothermal condition in the catalyst bed section was achieved by controlling the wall temperature of the reactor using TIC-202 and TIC-

203. The temperature profile inside the reactor was monitored using 1/8” five-point Omega temperature probe. The reactor assembly is illustrated in Figure 3-3.

Figure 3- 3: Reactor Assembly, adapted from Thiago Righi (Righi, 2016) 38

3.2.3 Separation Section

The separation section has a high-temperature and high-pressure vessel; (HTHP vessel), S-301,

which can operate at 300 °C and 400 psig to separate gases, lights and water from the heavy

hydrocarbon products. The gases leave the unit through back pressure valve, V-321, and the flow

is diverted either to GC for analyses or to the sour gas trap using valve V-322. The lighter

hydrocarbon along with water are collected in mass balance tank, MBT-303. The heavier

hydrocarbon products are collected in MBT-301.

Following the university guidelines, a Hazard and Operating Procedure (HAZOP) was completed

to recognize and eliminate the possible hazards associated with this unit. A copy of HAZOP

report is attached in the Appendix Section.

3.3 Experimental Procedure

The pilot plant described in Section 3.1 was used to test different catalysts and conditions for this

project. The procedure to prepare and mount the reactor is discussed in Section 3.3.1 and catalyst

treatment and reduction steps are described in Section 3.3.2. The methodologies used to start-up

and operate the reaction are given by Sections 3.3.3 and 3.3.4, respectively.

3.3.1 Reactor Filling

A representation of the packed bed reactor used in the experiments is shown in Figure 3-3. To

pack the reactor, the reactor exit (upper end) fittings, containing the thermocouple, were closed

and attached to reactor empty tubing. 80Mesh 0.12 mm wire size with 0.2 mm aperture was

inserted between the exit fitting and the tubing. This mesh acts as a dis-engager to keep the

carborundum and/or catalyst particles inside the reactor while letting the products exit the

reactor. Subsequently, the reactor was positioned upside down and a small amount of glass wool

was inserted at the exit (upper end) of the empty reactor. Then, a required amount of 39 carborundum (silicon carbide grains) were added until reaching the end of isothermal zone. After loading 10 g of the catalyst, the reactor was tapped to ensure particles were well packed. Another layer of glass wool was placed at the end of the catalyst bed to prevent catalyst particles removal with the fluid flow exiting the reactor. The remaining reactor volume was packed with carborundum and a thin layer of glass wool was placed on top. A piece of wire mesh was placed inside the entrance fittings before attaching it to the reactor. In principle, this mesh acted as a feed distributor similar to the nozzles in the commercial hydrocracking units. Finally, this fully assembled reactor was placed on the system for leak testing.

Leak tests were performed in the whole unit to ensure fittings were properly tightened. The unit was purged with nitrogen for 1hr before pressurizing it to 600 psig by closing the back-pressure valve, V-321. The maximum acceptable pressure-drop over a two-hour period was 1 %. All the leakages, if any, were identified and corrected. Consequently, another pressure test was performed until pressure drop limits were achieved.

3.3.2 Catalyst Treatment and Reduction

The molybdenum impregnated catalysts used in this project were thermally treated inside the reactor. For this purpose, the catalyst is passed through a thermal treatment, where the reactor temperature was ramped to 500 °C with 10 °C/min at ambient pressure under constant nitrogen flow of 50 mL/min using MFC-102. After reaching the set-point over the reactor wall temperatures, TIC-202 and TIC-203 were adjusted ensuring that all five internal temperatures, i.e., TI-202 – TI-206, were at the set-point. The reactor was held at 500 °C for five hours before lowering its temperature below 100 °C and nitrogen flow was stopped to start the reduction step.

All the catalysts went through same reduction step ensuring that metals in the catalyst were in their active reduced form before starting the reaction. The reduction temperature was obtained by

40 a temperature programmed reduction (TPR) experiment. TPR data reflected that 500 oC was a suitable reduction temperature for all catalysts used during this project. For catalyst reduction, the reactor temperature was ramped to 500 °C at 10 °C/min and ambient pressure under hydrogen flow of 50 mL/min. The reactor was held at 500 °C for 12 hours and then cooled down to ambient temperature. Finally, hydrogen flow was stopped, and the unit was purged with nitrogen for 1 h to ensure that the system was hydrogen free. A schematic representation of both steps is shown in Figure 3-4.

5hrs hold @ 500°C 12hrs hold @ 500°C

Step 1: Thermal Treatment Step 2: Catalyst Reduction Under 50ml/min Nitrogen at ambient Under 50ml/min Hydrogen at pressure ambient pressure

Figure 3- 4:Schematic representation of pre-treatment conditions 3.3.3 Reaction Start-up

A similar reaction start-up procedure was used for all the experiments carried out in the project.

The purpose of this step was to start the plant operation and bring all process variables to reaction conditions in a smooth manner.

3.3.3.1 System Purge and Unit Pressurization

After flushing the system with nitrogen, the unit was pressurized with this gas to reaction conditions, i.e., 400 psig by closing the back-pressure valve (V-322). The backpressure constrained the gas flow at the exit until pressure built up to the set-point value. After the system was fully pressurized, nitrogen flow rates were set to 5 ml/min to vessel S-301 to assist in separation of light hydrocarbon and water from the heavy products. This inert gas also helped in

41 recovering the unit pressure after the pneumatic valves open to drain products into the mass balance tanks. The reactor temperatures were steadily increased to desired reaction temperature at 10 oC/min ramp rate.

3.3.3.2 Steam Treatment

After reaching the set temperatures, steam was passed through the reactor for 3 hours at varying flowrate (VW) to saturate the catalyst pores with steam. The steam flow was controlled by setting the Teledyne Isco D-Series Syringe pump, P-103 flowrate in LabVIEW at flowrate calculated using Equation 3-1 and density of water at 15 °C = 0.9991 g/ml.

푎푚표푢푛푡 표푓 푐푎푡푎푙푦푠푡 푙표푎푑푒푑,푊 ( 푔) 푉 (푚푙⁄ℎ) = 푐푎푡 Equation 3- 1 푊,0 0.9991(푚푙⁄ℎ) 푋 3 (ℎ)

3.3.3.3 Oil Treatment

After 3 h of steam treatment and keeping the steam flowrate constant, either P-101 or P-102 was used to start flowing the oil through the system. The oil flowrates were set at 20 ml/h for 2 h to ensure all the lines leading to the reactor and the reactor were filled with oil.

3.3.3.4 Reaction Conditions

By the end of this step, both oil and water flow rates were set to the required flow rates. The oil flow rate, (Vo) was calculated based on the mass of catalyst, desired weight hourly space velocity

(WHSV), and oil density (휌표𝑖푙) using Equation 3-2. The water flow rate was calculated based on desired water-to-oil ratio (WOR) according to Equation 3-3. All the experiments presented in this thesis were carried out at WOR of 5.0 %vol.

−1 푊푐푎푡 (푔)×푊퐻푆푉 (ℎ ) 푉표 (푚푙⁄ℎ) = Equation 3- 2 휌표푖푙(푔⁄푚푙)

푉푤 (푚푙⁄ℎ) = 푉표 (푚푙⁄ℎ) × 푊푂푅 Equation 3- 3

The density of oil presented at pumps, P-101 and P-102 cylinders with a temperature of 100 °C was measured using Anton Paar DMA HP Density Meter following ASTM D-4052 method

(ASTM International, 2018). After establishing the desired oil and steam flowrates, the external reactor temperatures were adjusted in such a way that the average reactor temperature was within

±0.5 °C of the desired value.

Figure 3- 5:Schematic diagram summarizing the reaction start-up procedure

3.3.4 Reaction Operation

After establishing the steady state conditions as per Section 3.3.3, the products held in the high

temperature high pressure vessel, S-301. The Automated pneumatic valves (V-305 & V-307 for

heavy products and V-317 & V-318) installed in the separation sampling system open after a set

time interval to drain products from this HTHP vessel into the mass balance tanks (MBT-302

and MBT-303). The light hydrocarbon products and water from MBT-303 and heavier

hydrocarbon products from MBT-302 were collected in pre-weighed glass vails. The liquid mass

balances closure of 95 – 102wt.% were obtained except for the first mass balance, MB. The

process gasses were injected into a Gas Chromatograph (GC) for their compositional analyses.

3.4 Analytic techniques

The success of pilot studies depends on the robustness of the analytical methods used to

characterize the feed, product and catalyst. The data interpretation requires a thorough

understanding of the working principle of the equipment being used for the analysis and the

methods limitation. This section is divided into three sub sections: Liquid Hydrocarbon

Characterization, Process Gas Analysis and Catalyst Characterization to describe various

methods used during this project. Some of the results may not be shared because of the

confidentiality required for protecting the invention(s), nevertheless the techniques are still listed

and discussed.

3.4.1 Liquid Hydrocarbon Characterization

The sample collected from mass balance tank, MBT-303, had light hydrocarbons (light HC) and

water. This sample was stored in a freezer to separate the frozen water from the light HC. At

temperature below 0°C, water underwent a phase change from liquid to solid and light

HCremained in the liquid state. Using a syringe these light HC were added to the heavier

44 hydrocarbon(heavy HC) fraction. This mixture was then heated at 50°C under continuous stirring for 1-2 h to ensure homogenization. All the characterizations were carried on this homogenized sample.

3.4.1.1 High Temperature Simulated Distillation (HTSD)

The boiling point distribution of the feed and the products was determined via a high temperature gas chromatography following the ASTM-D7169 method (ASTM International, 2016). Agilent

Technologies Gas Chromatograph model 7890A with Simdist Expert software was used for determining the boiling point distribution up to 720°C. For this test, 0.15g of sample was dissolved in 20ml of carbon disulfide (CS2) and 1l of this solution was injected at the inlet of the GC. The inlet and a capillary column of the GC was heated from 50°C to 425°C, and -20°C to 425°C,respectively following a temperature program at 15°C/min ramp rate. A flame ionization detector operated at 435°C was used as a transducer to convert carbon mass to an electrical signal. These electrical signals were accumulated by Simdist Expert software to record peak intensities as a function of retention time. A reference standard with known boiling point distribution was used to find the boiling point corresponding to a specific retention time. The solvent injections were made to subtract the solvent response from the standard and the sample.

Studies have shown 3°C error in boiling point measurements and 1.58wt.% standard deviations in fractional yields (Raia, et al., 2000)(Austrich, et al., 2013).

3.4.1.2 Density and API Gravity

The density is an important physical property of the hydrocarbon for determining its economic value and must be specified during the trading and transportation via pipeline. It is also useful when comparing crudes from different sources. In the present work the density of the feed and products was measured using Anton Paar Laboratory Density Meter HP following the ASTM-

D4052 method (ASTM International, 2018). The densitometer is equipped with U-shaped oscillating sample tube, a system for electronic excitation, frequency counting, heating mechanism and a display.

A small amount of sample was injected into a U-shaped oscillating sample tube. The oscillation frequency of the sample tube along with the calibration curve determined the density of a sample

(Anton Paar, 2018).

American petroleum Institute gravity, API gravity is a quick way to compare different crude oil and its fractions. It compares the density of the hydrocarbons to the density of the water at 60 °F

(15.56 °C) (Petro Industry News, 2015).

The API gravity of the samples were calculated using the determined density for sample and the known water density.

141.5 퐴푃퐼 푔푟푎푣𝑖푡푦 = − 131.5 Equation 3- 4 푠푔푠푎푚푝푙푒 @ 15.60퐶

3.4.1.4 Total Acid Number

Acid Number analysis based on ASTM D-664 (ASTM International, 2017) has two test methods: test method A and test method B. Method A is used for petroleum products and lubricants with acidity in the range of 0.1 mgKOH/g to 150 mgKOH/g whereas method B is for biodiesels – and biodiesel blends with low acidity. The results for method A can be calculated in two ways, inflection endpoint and buffer endpoint whereas method B uses only automatic endpoint detection.

Inflection Endpoint: The quantity of base, potassium hydroxide (KOH) per gram of sample required to titrate a sample in the solvent from its initial meter reading in millivolts to a meter

46 reading in millivolts corresponding to a well-defined inflection point. Inflection point is the point where the slope of the first derivative curve changes from positive to negative direction or vice- versa (ASTM International, 2017).

Buffer Endpoint: The quantity of base, potassium hydroxide (KOH) per gram of sample required to titrate a sample in the solvent from its initial meter reading in millivolts to a meter reading in millivolts corresponding to a freshly prepared aqueous acidic buffer solution. A good electrode system should have a minimum potential difference of 162mV for pH 7 aqueous buffer. ASTM

D664 recommends using the buffer endpoint onlywhere no clear inflection point is detected

(ASTM International, 2017).

Mettler-Toledo T50 Titration Excellence apparatus was used to determine the total acid number

(TAN) results from the feed and the products. A sample was prepared by dissolving 1 g of sample in a 50:49.5:0.5 mixture of Toluene, Isopropyl Alcohol (IPA) and deionized water. This sample was titrated potentiometrically with alcoholic Potassium Hydroxide (KOH), using a combination

(glass/reference) electrode. The end-point was determined by Taimo 2.3 software at potential of

-220eV. Amount of KOH used to reach this end-point was calculated using Equation 3-5 and was reported as mgKOH/g sample. The results obtained during this project were within the reported reproducibility limit of 0.20mgKOH/g (Nadkarni, 2007).

푚푔퐾푂퐻 (푉 −푉 )(푚푙)푋 퐶 (푚표푙⁄퐿)푋푀푊 (푔⁄푚표푙) 푇퐴푁 ( ) = 푠 푏 퐾푂퐻 퐾푂퐻 Equation 3- 5 푔 표푓 푠푎푚푝푙푒 푊푠 where, Vsand Vb are the titrant volumes used for sample and blank, respectively, CKOH is the concentration of titrant solution and MWKOH is the molecular weight for Potassium Hydroxide, KOH

(Righi, 2016).

3.4.1.5 Carbon and Hydrogen

The carbon and hydrogen elemental contents of the samples were determined using EL cube:

Elemental Analyzer following ASTM-D5291 method (ASTM International, 2016). 2-3mg of sample weighted to the nearest 0.1mg was added to an alumina crucible and was fed into a combustion tube at 10500C. Helium gas was used to carry these combustion gases to a reduction tube where excess oxygen reacts with copper. This gas stream entered a gas chromatography column and the individual components are separated by elution in the order of nitrogen, carbon dioxide and water. The percentage of carbon and hydrogen was auto calculated by the operating software based on the area under the peak and the calibration data. The repeatability for this method was ±0.5wt.% for carbon and ±0.2wt.% for hydrogen.

3.4.1.6 Sulfur and Nitrogen

The sulfur content of the feed and liquid products was determined using an Antek model 9000

S/N Analyzer as per ASTM-D5453 (ASTM International, 2016). The sample solution was added to a sample boat at room temperature and the boat enters a high temperature (10750C) combustion tube. The sulfur present in the sample gets oxidized to sulfur dioxide (SO2) in the presence of oxygen. The gases are then exposed to ultraviolet (UV) light. After UV absorption

* SO2 is converted to excited sulfur dioxide (SO2 ). The photomultiplier tube detects the

* fluorescence emitted from the excited SO2 as it returns to a stable state. The results signals from the photomultiplier tube are proportional to the sulfur concentration in the sample. The repeatability and reproducibility of this method is 2.9% and 12.7%, respectively.

Nitrogen in the hydrocarbon samples was measured following ASTM-D5762 (ASTM

International, 2018). As mentioned in this method, the sample solution is placed in a boat that carries the sample to the high temperature combustion tube. The nitrogen present in the samples

48 gets oxidized to nitric oxide (NO) in oxygen rich environment. The NO gets converted to excited

* * NO2 in the presence of ozone. This excited NO2 emits light as it decays to stable NO2 state.

This emitted light gets detected by a photomultiplier tube and the resulting signals are proportional to the nitrogen concentration in the sample. This repeatability and reproducibility of this method are 8.7% and 26.6%, respectively.

A solution was prepared by dissolving 0.1 g of sample in 3 g of toluene and 5 µL of this solution was injected inside the combustion tube using an autosampler. Antek included software used the calibration data and peak areas to provide the sulfur and nitrogen concentration in the samples.

The sum of carbon (C), hydrogen (H), sulfur (S) and nitrogen (N) is subtracted from 100 to calculate the oxygen (O) content. Trace metals and other impurities are not considered since they make up less than 0.1wt% of the total bitumen feed(Speight, 2006).

푂 (푤푡%) = 100 − 퐶(푤푡%) + 퐻(푤푡%) + 푆(푤푡%) + 푁(푤푡%) Equation 3- 6

3.4.1.7 P-value

푃 − 푣푎푙푢푒 also called state of peptization of the oil sample is used as an indication of its stability

(ASTM International, 2018). The production of lighter paraffins and the increase in thermal cracking at higher reaction temperatures could cause the coagulation of asphaltenes molecules.

These conglomerates tend to drop out from the bulk fluid causing fouling in the reactors, pipelines and the storage tanks (Browarzik, et al., 1999). Equation 3-7 was used to calculate the

푃 − 푣푎푙푢푒 of the feed and the liquid products.

푃 − 푣푎푙푢푒 = 1 + 푋푚𝑖푛Equation 3- 7 where, 푋푚𝑖푛 is the Critical Cetane Dilution, the maximum milliliters of cetane with which one gram of test sample can be diluted without flocculation of the asphaltenes.

3.4.2 Gas Analysis

The products from the reactor outlet entered the high-temperature and high-pressure vessel (S-

301) where gases and light hydrocarbons along with water vaporize. These vapors were collected in low-temperature and high-pressure vessel (S-304). The process gas flow was measured, and then directed to a SRI model 8610C GC instrument. This GC has four different type of detectors;

Thermal Conductivity Detector (TCD), Flame Ionization Detector (FID), Flame Photometric

Detector (FPD) and Helium Ionization Detector (HID). The selection of the detectors depends on its sensitivity, selectivity, dynamic range, stability and repeatability (Buffington & Wilson,

1992). The detectors sense the presence of a component different from the carrier gas and transform that information into electrical signals. These electronic signals generate a chromatogram with peaks at different retention time on x-axis and peak intensity along the y- axis. The peaks in this chromatogram correspond to different species in the gas stream. These peaks are identified using a calibration standard gas mixture to determine the retention time for different gas species. The area under a peak is used for the quantification.

3.4.2.1 Thermal Conductivity Detector, TCD

As the name suggest, TCD responds to the difference in the thermal conductivity of the compound which is different from the carrier gas (Buffington & Wilson, 1992). Helium, He is used as a carrier gas because of its high thermal conductivity and chemical inertness. This detector is based on Wheatstone bridge circuitry, a voltage is produced due to the difference in the thermal conductivity of the column effluent (carrier and process gas components) and a reference flow of carrier gas only. The chromatographic software transforms these voltage changes to a chromatogram. The detector was calibrated using certified calibration gas mixture.

The relative errors between the certified and the measured composition is listed below in Table

3-2.

Table 3- 2: Relative Error in Gas Composition for GC Analysis using TCD detector

Component Relative Error (%) Component Relative Error (%)

Hydrogen, H2 3.6 Propene, C3H6 0.6

Methane, CH4 0.9 Propane, C3H8 0.9

Carbon Mono-oxide, CO 0.4 Iso-butane, i- C4H10 3.7

Carbon Dioxide, CO2 0.3 1-butene, CH2- C3H6 3.0

Ethylene, C2H4 0.4 n-butane, C4H10 1.5

Ethane, C2H6 0.3 Iso-pentane, C5H12 5.7

3.5 Catalyst Characterization

The catalysts used in this work were provided by a Postdoctoral Fellow, Dr. Gerardo Vitale.

Catalyst characterization is important to understand its physical and chemical properties

responsible for its performance in a given reaction (Bartholomew & Farrauto, 2006). The

preparation methodology, elemental compositions, and other properties are kept confidential.

Nevertheless, the various characterization methods used during this work are discussed below.

These techniques are widely used in the catalysis industry for quality control and manufacturing

cost optimizations.

3.5.1 Powered X-ray Diffraction (PXRD)

PXRD is the most common technique used to study qualitatively and quantitatively crystalline

structures of the catalyst material (Mulmi, 2016). The inter-planar distances between the

organized arrays of atoms in the crystalline structure can be calculated using Bragg’s law

(Equation 3-8),where n, d, ϴ and λ are integer, inter-planar distance, Bragg’s angle of diffraction and wavelength of X-ray, respectively.

푛휆 = 2푑푠𝑖푛훳 Equation 3- 8 The collision of X-rays with the electrons of the atoms present in a crystalline structure creates a diffraction pattern based on the inter-planar distance between the organized arrays of atoms in the crystalline structure. The different crystalline compounds present in the catalyst were identified by comparing them with a power diffraction database (Bartholomew & Farrauto,

2006).

These measurements were carried out in a Rigaku ULTIMA III X-ray diffractometer with Cu

Kα radiation located at the University of Calgary. The solids were measured in the range of 5-90

2θ degree at the count rate of 2 º/min and step of 0.02° at ambient conditions. This instrument has pre-installed JADE software which uses Scherrer equation to calculate the crystalline domain sizes (Vitale, 2013).

3.5.2 Surface Area, Pore Size and Pore Volume

Surface area, pore size and pore volume are important properties of the catalyst because they determine the accessibility of the active sites to the reactants and extent of diffusion of reactants and products between the catalyst pores, catalyst surface and the bulk fluid. The internal surface area of the catalyst is a function of the size and number of pores. The pore size distribution and the surface area need to be optimized for processing large molecules present in the bitumen.

These parameters were measured using N2 adsorption and desorption technique in a

Micrometrics Tristar 3020 equipment as per ASTM D3663 method. The equipment is designed to test three samples in each sequence. This method consists of three steps: sample preparation & pretreatment, setting up the measurement and data analysis.

Sample Preparation & Pretreatment: A small amount of sample (0.1-0.3 g) depending on the expected surface area of the catalyst being tested was placed inside a glass sample holder cell.

This cell was then heated up to 150 °C under continuous N2 flushing for a minimum of 12 h in a

Micrometric FlowPrep 060 apparatus.

Measurement Set-up: The glass cell containing the catalyst sample was removed from the

FlowPrep 060 and was secured to Tristar 3020 analyzer. A Dewar filled with liquid Nitrogen was used to maintain a constant temperature of 77K (-196 °C) in the cell. The partial pressure of N2 in the system was increased after predetermined time interval. These intervals were selected to provide enough time for N2 equilibration between the catalyst surface and the free space in the cell. The amount of nitrogen remaining after the sorption onto the surface of the sample was recorded as the function of N2 partial pressure. The process is then reversed by decreasing the pressure of the cell (Bartholomew, et al., 2006). This adsorption and desorption isotherms could result in hysteresis at higher partial pressures; for this reason, results obtained between partial pressures of 0.05 to 0.3 are considered more reliable (Bartholomew & Farrauto, 2006).

Data Analysis: The volume of nitrogen absorbed at a monolayer coverage (Vm) at a given partial pressure, x was determined using the Brunauer, Emmett and Teller (BET) equation.

푥 1 (푐−1)푥 = + Equation 3- 9 푉(1−푥) 푐푉푚 푐푉푚 where, V is the volume of N2 adsorbed at partial pressure, P and c is a constant that depends on the gas being adsorbed. Both,Vm and c can be calculated from the slope and intercept of the linear

푥 plot between and x. 푉(1−푥)

Vmis then corrected to STP condition, providing the volume of nitrogen absorbed/g of the

표 sample, 푉푚. BET surface area of the catalyst, SA was calculated using Equation 3-10.

2 표 훼 푆퐴(푚 ⁄푔) = 푉푚 ∗ 푁퐴푣 ∗ Equation 3- 10 푣0

23 where, 푁퐴푣 is Avogadro’s number (6.02*10 molecules/mole),훼 is surface area of nitrogen

-20 2 3 molecule (16.2*10 m /molecule); and푣0is the volume of gas/mol (22,400 cm /mole), respectively.

3.5.3 Temperature Programmed Techniques

Temperature programmed techniques were used to determine the reactivity and strength of interaction between the molecules and catalyst surfaces (Bartholomew & Farrauto, 2006). The three most commonly used techniques are Hydrogen Temperature Programmed Reduction (H2-

TPR), Ammonia Temperature Programmed Desorption (NH3-TPD) and Carbon Dioxide

Temperature Programmed Desorption (CO2-TPD). H2-TPR allows to determine the reducibility of the metals in the catalysts, on the other hand, NH3-TPD and CO2-TPD permits determination of the acidic and basic properties of a catalyst, respectively.

H2-TPR, NH3-TPD and CO2-TPD were done using a Quantachrome Chembet 3000 and following the same pre-treatment procedure, in which a known amount of sample was placed in a

U-tube and introduced into a temperature-controlled furnace.

Pretreatment of the samples was carried out by introducing argon gas at 15 ml/min through the tube at 200 °C for 1 h to remove air and physi-sorbed water molecules. After 1 h, the tube was cooled down to room temperature under argon atmosphere.

For H2-TPR, 10 vol.% hydrogen in argon was flowed into the tube and the system was heated to

500 °C at a rate of 10 °C/min. The hydrogen consumption was determined by measuring the exit gas composition using thermal conductivity detector (Vitale, 2013). H2-TPR provided the reduction profile for the catalyst and was used to determine the temperature required in the catalyst reduction step before starting the reaction.

For NH3-TPD, 10 vol.% of NH3 in helium was flowed into the system for 1 h to allow at ambient conditions the chemisorption of the NH3 molecules onto the acidic sites of the catalyst.

Subsequently, the furnace at about 200 °C and pure helium was flowed through the system to remove the excess of the gas that was not adsorbed. The furnace temperature was increased to

500 °C at a rate of 10 °C/min afterwards and the amount of NH3 desorbed was recorded as a function of temperature (Vitale, 2013). In NH3-TPD, the basic molecule (NH3)interacts with the acidic sites of the catalyst surface. The NH3-TPD data can be used to quantify the total amount of acid sites and strength, regardless of their type (Lewis or Brønsted).

In CO2-TPD, CO2 instead of NH3 was used and the procedure was the same as described for

NH3-TPD. The data from CO2-TPD was used to quantify the total amount of basic sites and strength, regardless of the type (Lewis or Brønsted) (Vitale, 2013).

3.5.4 Thermogravimetric Analysis (TGA)

TGA measures the change in the weight of a substance with increase in the temperature. Few milligram of fresh catalyst sample was placed in the ceramic crucible before loading it in the heating chamber of Thermal Analysis Instruments DT Q 600. The sample was subjected to dynamic heating at a heating ramp rate of 20 °C/min up to 800 ºC under a nitrogen flow (100

Std. ml/min). The weight loss was recorded as a function of increasing temperature. This data was used to calculate the moisture content in the catalyst used during this project. In addition, no weight loss at elevated temperature indicated that the catalysts were thermally stable.

3.5.5 Metal analysis

The metallic composition of catalyst is essential to confirm the accuracy of its preparation and metal quantification. This analysis consists of two steps: an initial sample digestion and an

Inductively Couple Plasma (ICP) analysis.

The sample digestion was done by mixing 0.3 g of sample with 10.5 ml of nitric acid, 1 ml of phosphoric acid and 25 μ l of a 1000 ppmw cobalt internal standard in Teflon cells used a

Microwave Accelerated Reaction System (MARS model MARS 6). The digested sample was then diluted to a pre-determined volume to prepare a solution for ICP analysis. A sample aliquot from this solution was analyzed in an ICP-Atomic Emission Spectrometer (AES) model IRIS

Intrepid II XDL from Thermo Scientific. The peristaltic pump delivers the sample to the analytical nebulizer where it vaporizes. The collision of the molecules with the electrons and other ions in an Argon plasma flame disintegrate them into their respective atoms. The atoms lose electrons and recombine with other atoms inside the plasma flame giving of radiation of characteristic wavelength. The peak intensity at a given wavelength is then compared to the calibration data to calculate the concentration of metals in the test sample (ASTM International,

2018).

Chapter 4: Results and Discussion

This chapter is divided in eight main sections. The catalyst characteristics are presented in the first section; the pilot plant operation, thermal run and catalytic runs are summarized and discussed in the second, third and fourth section, respectively. The fifth section includes the discussion on the performance of different catalysts, and evaluation of kinetic parameters for hydrocracking reactions associated with these catalysts. The mass transfer limitations for Cat J17 are discussed in the sixth section. The dimensionless numbers and hydrodynamic properties are covered in the last two sections.

4.1 Catalyst Characterization

The performance of any catalytic upgrading technology would fundamentally depend on the catalyst used to breakdown heavier oil molecules. The catalyst selection requires a thorough understanding of the feedstock, desired product yield distributions, reactor design, normal operating range and target cycle length (Gaigneaux, et al., 2002). The experimental work carried out for optimizing the catalyst preparation techniques and their physicochemical characteristics for Aquaprocessing was discussed by Eduardo Garcia-Hubner, Thiago Righi, Fredy Navarro and

Lorena Bernal-Sardi (Garcia-Hubner, 2015) (Righi, 2016) (Navarro, 2016) (Bernal-Sardi, 2017).

Two types of catalysts: Catalyst H-2 and Catalyst J were used in this study. The precursor for

Catalyst H-2 was manually cut into two different size ranges (1-2mm and 3-5mm) before calcination and molybdenum impregnation. The Catalyst H-2 with particle size between 1 to 2 mm and 3 to 5 mm will be referred as Cat H-2.1 and Cat H-2.2, respectively from this point forward. Catalyst J was prepared via wet impregnation method using 1 mm (Cat J15) and 2.5 mm (Cat J17) alumina spheres. The textural and structural properties of these catalysts were

57 monitored at various stages throughout the preparation steps. The XRD diffraction patterns of the pair Cat H-2.1 and Cat H-2.2;and the pair Cat J15 and Cat J17 were identical among them showing that both catalyst types have similar crystalline phases.

As expected, the change in the catalyst particle size resulted in some variations in their textural properties. These differences are summarized below in Table 4-1.

Table 4- 1: Textural Properties of the Catalysts Properties Cat H-2.1 Cat H-2.2 Cat J15 Cat J17 Wet- Wet- Preparation Method Co-precipitation Co-precipitation impregnation impregnation Shape Cylindrical Cylindrical Spherical Spherical L=1.63±0.37 L=4.56±0.61 *Dimensions (mm) D=1.0±0.05 D=2.5±0.05 D=1.65±0.03 D=1.65±0.03 Surface Equivalent 2.01 2.98 - - Sphere diameter (mm) BET Surface area(m2/g) 104 90 122 113 Pore volume (cm3/g) 0.43 0.38 0.29 0.25 Average pore width (Å) 110 134 87 77 Type of porosity Bimodal Bimodal Unimodal Unimodal Main pore width (Å) 30 and 330 30 and 330 65 70 *Dimensions: 100 random particles were measured using a Vernier caliper and average is reported.

A Vernier caliper was used to measure 100 random particles from each of these catalysts and their average is reported in the table above. The size variation for Catalyst J was small because it was prepared using commercial alumina spheres, whereas the large variations in the length of

Cat H-2.1 and Cat H-2.2 were due to the limitations associated with the in-house method used for cutting the extrudates. The surface-equivalent sphere diameter (DS) was calculated using

Equation 4-1 where, l and dex are average length and diameters of extrudates, respectively.

1 0.5 퐷 = ( 푆푢푟푓푎푐푒 푎푟푒푎 표푓 푡ℎ푒 푐푦푙𝑖푛푑푟𝑖푐푎푙 푝푎푟푡𝑖푐푙푒) 푆 휋

1 푑 0.5 퐷 = ( × (휋푑 ( 푒푥 + 푙)) 푆 휋 푒푥 2

0.5 푑푒푥 퐷푆 = (푑푒푥( + 푙)) Equation 4- 1 2

The Tristar 3020 software calculate the cumulative volume of pores of width between 1.7 nm and 300 nm based on Barret, Joyner and Halenda (BJH) model (Groen, et al., 2003). Pore volumes of Cat H-2.1 and Cat H-2.2 were significantly higher than Cat J15 and Cat J17 because of their wider pore abundance in the mesoporous region. The co-precipitation preparation technique provided Cat H-2.1 and Cat H-2.2 their bimodal pore distribution, whereas, the unimodal pore distribution with pore size relatively smaller than Cat H-2.1 and Cat H2.2 for Cat

J15 and Cat J17 derived from their gamma alumina support.

For all catalysts, H2-TPR profile showed active metals were in their reduced form in the temperature range of 350-500 °C. Based on this analysis, the reduction temperature of 500 °C was selected during the reaction start-up for all the catalysts. NH3-TPD and CO2-TPD comparison between Cat H-2.1 and Cat H-2.2 displayed similar acidity and basicity; whereas Cat

J17 had more than double the number of acid sites and 60% more basic sites than Cat J15. Al3+ and O2- were the major source of acidic and basic sites, respectively, in these catalysts (Prinetto, et al., 2000). These results indicated that the percentage of exposed alumina was higher in Cat

J17 than in Cat J15. The presence of these acid and basic sites in proximity to each other within the crystalline lattice structure of the catalyst is essential for its application in hydrocracking of petroleum fractions. The extent of hydrogenation and decarboxylation is controlled by the strength and number of the basic sites (Ancheyta & Speight, 2008) (Hattori, 1995). The acid sites

59 are critical for cracking of heavier hydrocarbons into lower molecular weight molecules, but their excess could result in coke formation via polymerization.

4.2 Pilot Plant Operations

Pilot plant set-up described in Section 3.2 was used to carry out all the experimental work. The operation procedure was followed to perform mass balances (MBs) after every 24 h to collect liquid products. As mentioned in Section 3.3.4, the light oil and water were collected from MBT

- 303 and the heavy oil was collected from MBT - 301. The sample vial containing light oil and water was stored in a freezer to separate the light oil (organic) and water (ice). This light oil product was mixed with heavy oil product under vigorous stirring for 2 h at 50 °C to produce homogenized synthetic crude oil (SCO). Furthermore, the SCO was later characterized using various analytical techniques as described in Section 3.4.1. Four MBs were performed at each reaction temperature. The first MB after the condition change was considered as stabilization period and the results obtained from the sample collected during this MB were not included in the data analysis. The average results for the last three mass balances at each test conditions are reported in this chapter. GC analysis was carried out to measure the product gas composition but not considered in the mass balance closures because of the poor reproducibility. Test program listed in Table 4-2 was followed to complete the experimental studies.

Table 4- 2: Pilot Plant Test Program for Catalysts Performance Comparison

Run Time on stream Run WHSV WOR Temperature Pressure # (h) Type (h-1) (m/m) (°C) (Psig) 96 350 192 360 1 Thermal -- 5:100 400 288 370 384 380

96 350 192 360 2 Cat H-2.1 0.25 5:100 400 288 370 384 380

96 350 192 360 3 Cat H-2.2 0.25 5:100 400 288 370 384 380

96 350 192 360 4 288 Cat J15 0.25 5:100 370 400 384 380 480 390

96 350 192 360 288 370 5 Cat J17 0.25 5:100 400 384 380 480 390 528 370

4.3 Thermal Run

A thermal run was carried out to distinguish the catalytic effect on TAN reduction, viscosity

reduction, sulfur removal and VR conversions from thermal upgrading process. The analytical

results obtained from characterization of thermally upgraded SCO were used as a baseline for the

catalyst evaluations.

In this run, the reactor was filled with washed carborundum (silicon carbide) particles. The 2 - 3

mm size of these irregular shaped inert grains ensured that the flow patterns and residence time

during the thermal run would be same as expected during the catalytic runs. The bitumen and

steam flow rates were calculated using the procedure described by Garcia-Hubner assuming 10 g

of the catalyst will be loaded for the catalytic runs (Garcia-Hubner, 2015). The average of the

last three MBs’ at each reaction condition are reported below in Table 4-3.

Table 4- 3: Analytical Results for Thermal Run at 3.7 h Residence Time

Average Reaction Temperature, °C 350 360 370 380 Products FEED SCO SCO SCO SCO Density kg/m3 1002.1 1011.9 1003.8 1001.3 995.6 API ° 9.7 8.3 9.5 9.8 10.6 Dynamic Viscosity cP 67700 48802 14723 6557 4818 TAN content mgKOH/g 2.34 1.30 1.23 1.57 1.47 Conversions Dynamic Viscosity Reduction % 27.91 78.25 90.31 92.88 TAN reduction % 44.65 47.4 32.72 37 Vacuum Residue Conversion % 0 3.56 11.03 11.07 Sulfur Removal % 0 0.73 3.41 5.11 *400 psig, 2.67 ml/h oil flowrate and WOR of 5:100 (m/m) At the low severity, i.e. 350 °C – 380 °C, maximum of 11 wt.% VR conversion was achieved

without any evidence of coke formation. These conversions were in close agreement with 10-20

wt.% conversion reported at 400 - 430 °C(Huc, 2011). Thermal decomposition of weak acidic

molecules resulted in 32 – 45 % reduction in TAN content. A maximum of 5 wt.% sulfur

removal was calculated for SCO obtained at the reaction temperature of 380 °C. The mild

cracking of the heavier hydrocarbons to form lighter fractions (Figure 4-1) resulted in

exponential decay in the SCO viscosity with increase in the reaction temperature. Similar trends

in the viscosity reduction have been reported by Rodriguez-DeVecchis during thermal upgrading

of bitumen in porous media (Rodriguez-DeVecchis, et al., 2017).

Figure 4- 1: Product Distribution for Thermal Cracking

As shown in Figure 4-1, a small decrease in the naphtha, kerosene and diesel fraction because of the uncontrolled losses of the light ends at lower reaction temperature increased the density of the SCO by 10 kg/m3 in comparison to the feed. A sample drainage line was added to the outlet of valve (V-309) to avoid such losses during the subsequent mass balances. The overall trend showed a slight increase in naphtha, kerosene, diesel and LGO fraction with the increase in the reaction temperature from 350 to 380 °C. The fluctuation in the VGO content was likely due to the secondary cracking of VGO into lighter fractions (Cabrales-Navarro & Pereira-Almao,

2017). Any anomalies were within ±2 wt.% error associated with the use of simulated distillation methods for yield determination. The limitations associated with the blending technique used for mixing light and heavy products was a main source of uncertainties.

4.4 Catalytic Runs

The four catalysts: Cat H-2.1, Cat H-2.2, Cat J15 and Cat J17 were tested at the reaction conditions listed in Table 4-1. A fixed amount (10 ± 0.1 g) of catalyst was loaded into a 11.8” long stainless steel (SS 316) reactor of 0.43” (1.09 cm) internal diameter as described in Section

3.3.1. These catalysts were subjected to pretreatment and reduction conditions and the reaction start-up procedure (Section 3.3.2). The in-situ thermal treatment under constant inert gas environment(N2) at 500 °C was carried out to ensure formation of Mo2C. The use of Mo2C in hydrogenation reaction is widely reported (Perez Zurita, et al., 2015) (Clair, et al., 1999). The comparison studies carried out by Guzman showed the activity of Mo2C is similar to noble metals (Pt, Pd) for hydrogenation applications (Guzman Gomez, 2014). Further, flow was switched to H2 and the reactor was held at 500 °C to perform catalyst reduction.

Steam treatment (Section 3.3.3) before introducing bitumen to the reactor was extremely critical for these Aquaprocessing reactions. This procedure ensured the in-situ production of hydrogen via CSC before starting the thermal and/or catalytic cracking of hydrocarbon molecules.

Cracking in the absence of hydrogen can cause coke formation via condensation and polymerization of the unsaturated hydrocarbons. The deposition of this coke on the active sites and the catalyst pores is a known source for catalyst deactivation (Hopkins, et al., 1996). After the steam treatment, bitumen flow was started, and steady operation conditions were established as per Section 3.3.4.

All the experiments were carried out at 0.25 h-1 WHSV, water to oil ratio (WOR, m/m) of 5:100 and 400 psig pressure. The reaction temperature was increased by 10 °C after every 96 h from

350 °C to 380 °C for Cat H-2.1 and Cat H-2.2, and from 350 °C to 390 °C for Cat J15 and Cat

J17, respectively. A tie-back period was introduced during Cat J17 testing to check for catalyst

64 deactivation. The maximum reaction temperature for Cat J15 and Cat J17 was increased to check if VR conversions can be increased further without causing instability in synthetic crude oil

(SCO). The upgraded products, SCO, were characterized and the detailed analytical results obtained for Cat H-2.1, Cat H-2.2, Cat J15 and Cat J17 are listed in Appendix Bas Table B-1, B-

2, B-3 and B-4, respectively. The four properties of SCO: (i) Total acid number (TAN), (ii) viscosity, (iii) sulfur and (iv) VR content were monitored throughout these catalyst evaluation runs for comparative studies and this experimental data is discussed below.

4.4.1 Total Acid Number (TAN) Reduction

TAN is a measurement used in the oil industry to determine the acidity of a crude oil and its fractions. Acidity of crude oil is related to its naphthenic acid content(Speight, 2014). These acids are known for causing corrosion at refineries and upgraders in the distillation towers, desalters and heat exchangers. The alkaline earth-metal oxide, magnesium oxide (MgO) present in selected types of Aquaprocessing catalysts provides the sites required for the adsorption and further decomposition of acid species including naphthenic acids via catalytic decarboxylation reaction (Equation 4-2). These hydrocarbon molecules with carboxylic groups react with water molecules to produce lower molecular weight hydrocarbons and gases such as hydrogen (H2) and carbon dioxide (CO2).

퐶푛퐻푥 − 퐶퐻2 − 퐶푂푂퐻 + 2퐻2푂 → 퐶푛퐻푥+1 + 2퐶푂2 + 3퐻2 Equation 4- 2 The experimental results for TAN reduction are presented in Figure 4-2. The calculated error bars are based on 5 % repeatability limits of the test method. These results reflect that 100% removal of acidic species was attained at reaction temperatures of 370°C and above for Cat H-

2.1 as well as Cat H-2.2. Similar results were reported in the dissertation of Righi (Righi, 2016).

For Cat J15, TAN reduction increased almost linearly with increase in reaction temperature

65 giving a maximum of 82 %TAN reduction at 390 °C. Similar results were reported for alkaline earth-metal oxides catalysts such as magnesium oxide, calcium oxide and barium oxide(Lianhui, et al., 2009)(Ding, et al., 2009). Cat J17 displayed extremely high activity in the beginning of the reaction and showed a significant drop for next two test conditions – indicating catalyst deactivation; but, interestingly it regained its acid removal strength at 380 °C showing some of the active sites for decarboxylation reactions were accessible again. No clear explanation for this behavior is known yet, however, high basicity and high acidity of Cat J17 are speculated as potential causes.

Figure 4- 2: Performance of Aquaprocessing Catalysts - Total Acid Number (TAN) Reduction

Acidic crudes such as Athabasca bitumen (2.5 mgKOH/g) are penalized at an estimated rate of

US$0.88 per unit of TAN above 0.5 mgKOH/g TAN threshold (Bacon & Tordo, 2004). The

SCO produced via Aquaprocessing using catalyst either Cat H-2 or Cat J15at reaction

66 temperature of 370 to 390 °C would increase the net margin for the upgrading facility by US$

1.76/bbl.

4.4.2 Viscosity Reduction

Viscosity reduction is one of the major advantages of Aquaprocessing technology for its field upgrading application. As discussed in Section 2.2, the heavy oils are currently blended with condensates for meeting the pipeline specifications.

Figure 4- 3: Performance of Aquaprocessing Catalysts - Viscosity Reduction

As shown in Figure 4-3, an exponential increase in the viscosity reduction was observed with an increase in the reaction temperature. Garcia-Hubner and Righi have reported similar trends for

Aquaprocessing of de-asphalted oil (DAO) and dilbit, respectively in their dissertations (Garcia-

Hubner, 2015) (Righi, 2016). The conversion of vacuum residue to lighter hydrocarbons such as naphtha, kerosene, diesel and gasoil increased with the rise in reaction temperature. These lighter

67 fractions lower the viscosity of the oil. A maximum reduction in viscosity (98 %) was achieved for Cat J15 at 390 °C reaction temperature.

Based on Lederer’s empirical correlation (Equation-4.3 and Equation-4.4) for calculating the blend viscosity (, this upgraded product would require only 14 to 16vol.% condensate compared to 33 vol.%. required for Athabasca bitumen to meet the viscosity constraint of 350cSt at the pipeline temperature(Huc, 2011). This would increase the heavy oil shipment by at least

15 % via existing pipeline infrastructure and would also eliminate some of the cost associated with the diluent requirements to meet the pipeline specifications.

훼푉0 훼푉0 푙표푔 휇 = 푙표푔휇0 + (1 + ) 푙표푔휇 Equation 4- 3 훼푉0+ 푉푠 훼푉0+푉푠

0.5237 3.2745 1.6316 17.04(휌0−휌푠) 휌0 휌푠 훼 = 휇 Equation 4- 4 푙푛 0 휇푠 where, V and describes viscosity, volume fraction and density, respectively. The subscripts

(O) and (S) are used to specify oil and solvent, respectively.

4.4.3 Hydrodesulfurization (HDS)

Heavy oils are also referred as sour crude oils because of their high sulfur content (>0.5 wt.%)

(Speight, 2006). The stringent environmental regulations and processing of sour gas streams adds to the operational cost for the refineries.

The hydrogen produced via steam cracking reaction aided in sulfur removal from organosulfur compounds. The experimental results are presented below in Figure 4-4. HDS level increased almost linearly with increase in the reaction temperature during both catalytic and thermal runs.

The observed sulfur removal was very low as compared to the industrial Ni-Mo or Co-Mo

68 catalysts (Fahim, et al., 2009). The present study suggests that sulfur removal can be increased by compositional improvements to Cat H-2 and Cat J15.

Figure 4- 4: Performance of Aquaprocessing Catalyst-HDS

Cat H-2.1 and Cat H-2.2 consistently outperformed Cat J15 by 8 to 10 %. The high error in HDS determination derives from the analytical method used for measuring sulfur content in the products. The sulfur content in SCO from Cat J17 was not measured because of the instrument breakdown. A maximum of 21 % reduction in sulfur content would lower the crude penalties by

US$ 1.5/bbl. (Canadian Association of Petroleum Producers, 2018).

4.4.4 Hydrocracking* (HCK*)

Typical hydrocracking reaction takes place at high reaction pressure in the presence of hydrogen, whereas, in Aquaprocessing in-situ generated hydrogen from steam cracking reaction is used to hydrogenate free radicals formed from thermal and/or catalytic cracking of heavier hydrocarbons

(Pereira-Almao, et al., 2013). The extent of cracking reaction depends on reaction temperature

69 and the number and the strength of the acid sites that are accessible to the heavy hydrocarbon molecules.The vacuum residue conversions, i.e., HCK* are presented below in Figure 4-5.

Figure 4- 5: Performance of Aquaprocessing Catalyst–HCK*

HCK* activity of Cat H-2.1 and Cat H-2.2 was slightly better than Cat J15 for reaction temperature below 380 °C and above this temperature Cat J15 still provided good HCK*. The

VR conversions for Cat J17 were consistently lower than the other three catalysts used in this study. The average pore width of 77 Å indicates that this catalyst had relatively narrow pores compare to other catalysts (Table 4-1). These narrow pores in Cat J17 are likely to plug faster than in Cat J15 and Cat H-2. The catalyst characterization showed higher acidity and basicity for

Cat J17 than in Cat J15 which also indicate coke deposition could have deactivated the catalyst.

To rule out this hypothesis, the reaction temperature was lowered to 370 °C at the end of the run.

The results from this tie-back period along with MB#10, MB#11 and MB# 12 are listed in Table

4-4. The Tie-back period results were similar to those obtained during the other mass balances at the similar test conditions.

Table 4- 4: Tie-Back Period Results for Cat J17

Properties Units MB#10 MB#11 MB#12 MB#22 (Tie-back)

Dynamic Viscosity cP 4868 4458 4513 4160 at 25 °C Total Acid Number, mgKOH/g 1.81 1.63 1.72 1.50 TAN VR Fraction, 550 wt.% 45.70 43.12 44.44 43.55 °C+

In summary, the similar VR conversions and other properties of SCO for Cat H-2.1 and Cat H-

2.2 indicate that the catalyst particle size had no impact on the performance of the catalyst prepared using co-impregnation method. The active metals are well dispersed throughout the bulk, pores and surface of the catalyst. The presence of pores in upper mesoporous range (15 - 50 nm) make these catalysts less prone to both external and internal mass transfer limitations, as they are quite large compare to the size of the asphaltene molecules (Groenzin & Mullins,

2000).On the other hand, conversions obtained for catalysts prepared via wet impregnation method (Cat J15 and Cat J17) were quite different. The vacuum residue conversion for Cat J17 was consistently lower than J15 and catalysts Cat H-2.1 and Cat H-2.2, most probably because of external mass transfer limitations.

4.5 Kinetic Analysis for Hydrocracking* Reaction

The kinetic rate constants (k’) for HCK* for all the catalysts were calculated using Equation 2-

39. These results along with other parameters required for calculating the pre-exponential factors and activation energies of the four catalysts are listed below in Table 4-5.

Table 4- 5: Kinetic Rate Constants for Hydrocracking* of Vacuum Residue

Catalyst Catalyst Bulk Reaction Vacuum Residue Kinetic Rate

Density, c(g/ml) Temperature, T Conversion, X (%) Constant, k' (°C) (dm3h-1kg-1) 350 10.87 0.0302 360 15.02 0.0428 Cat H-2.1 0.725 370 21.34 0.0631 380 29.25 0.0909 350 11.26 0.0314 360 14.82 0.0421 Cat H-2.2 0.747 370 21.94 0.0651 380 27.67 0.0851 350 13.47 0.0380 360 16.94 0.0487

Cat J15 1.090 370 20.65 0.0608 380 26.04 0.0792 390 33.60 0.1076 350 3.05 0.0081 360 8.87 0.0244

Cat J17 0.958 370 12.24 0.0343 380 19.01 0.0554 390 19.31 0.0564

The kinetic parameters: pre-exponential factor (k0) and the activation energy (Ea) for these catalysts were calculated using the Arrhenius Equation (Equation 4-5).

−퐸 ( 푎) 푘 = 푘0푒 푅푇 Equation 4- 5

Taking ln on both sides of Equation 4-5

퐸 푙푛(푘) = 푙푛(푘 ) − ( 푎 ) Equation 4- 6 0 푅푇

The ln (k) vs 1/T plot also known as Arrhenius plot were used to calculate the kinetic parameters.

Figure 4- 6: Arrhenius Plots for Hydrocracking* (HCK*) Reaction in Aquaprocessing

These Arrhenius plots (Figure 4-6) show that the hydrocracking of vacuum residue (VR) fraction for Cat H-2.1, Cat H-2.2 and Cat J15 fit the linear regression line very well with R- squared (R2) value above 0.99 in all three cases. These results validate the assumption made in

Section 2.7.4 for the derivation of design equation (Equation 2-37) for packed bed reactor. The unexpected trendfor VR conversions obtained during Cat J17 testing resulted in a poor fit with

R2 value of 0.84. The kinetic parameters obtained from these linear plots are listed below in

Table 4-6.

Table 4- 6: Kinetic Parameters for Hydrocracking of Vacuum Residue in Aquaprocessing

Universal Gas Activation Energy, Pre-exponential Factor, Intercept Catalyst Slope Intercept Constant, R Ea= - slope*R k0=e (kcalK-1mol.-1) (kcal/mol.) (dm3h-1kg-1)

Cat H-2.1 -15020.2 20.59 29.83 8.76E+08

Cat H-2.2 -13942.0 18.90 27.69 1.61E+08 0.001986 Cat J15 -10590.9 13.70 21.03 8.94E+05

Cat J17 -19498.2 26.80 38.72 4.35E+11

The co-precipitation method used during synthesis of Cat H-2.1 and Cat H-2.2 provided them with same type of the active sites which is reflected by similar activation energy for these catalysts. In catalytic reactions, the pre-exponential factor (k0) is usually reflective of the number of the active sites available for reaction. The higher number of the catalyst particles per unit mass for the catalyst with smaller extrudate length would result in higher surface area and consequently more active sites. For this reason, Cat H-2.1 had higher k0 value than Cat H-2.2.

The lower Ea for Cat J15 than Cat H-2 suggests poor internal mass transfer may be taking place in Cat J15; the lower pre-exponential factor is also suggesting of fewer sites were accessible.

These results are in agreement with pore width data obtained from the BET analysis (Table 4-1).

The average pore width (8.7 nm) for Cat J15 was only two to three times the size of an asphaltene molecule. A binding of an large size molecules such as asphaltene to an active site at the mouth of these small size pores restrict the entrance of other heavier hydrocarbon molecules inside them. Because of this phenomenon the active sites present inside these relatively small pores were not used in the reaction as reflected by lower k0 value.

The poor curve fit for Arrhenius plot for Cat J17 indicates vacuum residue conversion for Cat

J17 was following a different path, perhaps thermal cracking on acid sites. As explained in

Section 2.7.5, the kinetic rate constant (k') depends on kinetic rate constant for the surface

′ ′ reaction (푘푟) and the modified mass transfer coefficient (푘푚),at higher reaction temperature

′ ′ ′ ' ′ 푘푟has grown faster such that푘푟>>푘푚 then k 푘푚 as per Equation 2-40(Smith, 1970).

1 1 1 ′ ′ = ′ + ′ ; 푘푚 = 푘푚푎푚 푘 푘푚 푘푟

As displayed in Figure 4-7, the Arrhenius plot for Cat J17 was divided into three regions based on the slope of the curve. The variation in the slope of the Arrhenius plot suggests that the rate determining step for vacuum residue conversion was changing with the reaction temperature.

Region 1 and Region 3 have only two data points, having additional data in future studies would be useful to confirm these observations.

Figure 4- 7: Mass Transfer Limitations associated with Cat J17 The activation energy and the pre-exponential factors obtained using the slopes and intercept for these three regions are listed in Table 4-7.

Table 4- 7: Cat J17 Performance

Region # Activation Energy, Pre-exponential Factor, Intercept Reference to Ea= - slope*R k0=e Rate limiting Step Figure 4-7 (kcal/mol.) (dm3h-1kg-1)

Overall 38.72 4.35E+11 Not clear Surface Reaction Region 1 85.94 1.17E+28 Catalyst Highly active Surface Reaction Region 2 33.62 9.78E+09 Decay in Catalyst Activity Region 3 1.52 1.79E-01 External Mass Transfer

The extremely high Ea at the beginning of the run for Region 1, between reaction temperatures of

350 °C and 360 °C, indicates either the Cat J17 was very active or the reaction was proceeding via thermal cracking mechanism. The NH3-TPD data showed Cat J17 had twice the acidity of

Cat J15 – this higher acidity is believed to be the cause for this higher activity.

In Region 2, the activation energy and the pre-exponential factor were similar to Cat H-2. This indicates that the reaction rate was controlled by the surface reaction as it was in case of Cat H-

2.1 and Cat H-2.2.

In Region 3, Ea and k0dropped way below the catalytic hydrocracking reaction limits as well as those obtained for the other three catalysts (Moghadassi, et al., 2011)(Gao, et al., 2014). These observations suggest that the external mass transfer resistance was the rate limiting step at the higher reaction temperatures.

4.6 Mass Transfer Limitations

′ Ideally, the surface reaction kinetic rate constants (푘푟) can be obtained by carrying series of experiments at different residence time and reaction temperatures in a continuous stirred tank reactor (CSTR) where mass transfer limitations can be eliminated. In the present work, since

76 difference in the particle size between Cat H-2.1 and Cat H-2.2 did not show any significant impact on VR conversions, it was assumed that in the absence of mass transfer limitations the

′ true surface kinetic rate constants (푘푟) would be similar as kinetic rate constant (k’) calculated

2 for Cat H-2.1.The external surface area, am (0.0025 m /g) was used to calculate the mass transfer coefficient(km) for Cat J17.

Table 4- 8: Evaluation of Mass Transfer Coefficient

Modified Mass Reaction Kinetic Rate Kinetic Rate External Mass Transfer Transfer Temperature, Constant for Constant for Surface Area Coefficient for Coefficient for ' - T Cat J17, k Cat H-2.1, of Cat J17, Cat J17, km(cms cat J17, 3 -1 -1 ' 3 -1 -1 2 1 (°C) (dm h kg ) k (dm h kg ) am(m /g) ) ' 3 -1 -1 km (dm h kg ) 350 0.0081 0.0302 0.0112 1.239E-07

360 0.0244 0.0428 0.0568 6.314E-07 0.0025 370 0.0343 0.0631 0.0753 8.361E-07

380 0.0554 0.0909 0.1417 1.574E-06

These calculated mass transfer coefficients for diffusion of steam in bitumen were similar to the mass transfer coefficient reported by Etminan for diffusivity of carbon dioxide (CO2) and methane diffusion in bitumen(Reza Etminan, et al., 2014).

Figure 4- 8: Variation in Mass Transfer Coefficient with Reaction Temperature

4.7 Evaluation of Sensitivity Parameters

The impact of changing any operating parameters such as flow rates, temperature and pressure and the catalyst particle size on the conversions can be evaluated using dimensionless numbers such as Schmidt number (Sc), Reynolds number (ReLfor liquid phase and ReG for gas phase)(Ross, 2012). The variables required to calculate these dimensionless numbers were obtained from a process simulation software (ProMax) using Peng Robinson equation of state environment. It was assumed that dynamic viscosity, density and volumetric flow rates of vapor and liquid phase inside the reactor will besimilar to those obtained for bitumen with 4.8 wt. % water. The effect of reaction rate on these parameters was not considered for evaluation of these properties.The predicted physical properties such as dynamic viscosity and density may not be entirely correct, but the obtained trends should be (Appendix D).

Based on the reported values for spherical particles, bed porosity ( was assumed to be 0.4

(Khirevich, et al., 2011). The other required variables were mentioned throughout this report

78 namely; catalyst bulk densityc) and the diameter of the catalyst particles (dp) ofCat J15 and

Cat J17 are 1.09 g/ml and 0.96 g/ml; and 0.1 cm and 0.25 cm; respectively; inside diameter of the reactor, dT(1.09 cm); reactor length, L (30 cm). Based on the vapor and liquid phase compositions; water (vapor phase) diffuses through the oil (liquid phase) to react with the oil molecules on the catalyst surface.

Schmidt number, Sc is a ratio of momentum diffusivity to molecular diffusivity, used for the system with simultaneous momentum force and mass transfer(Usabiaga, et al., 2013). The diffusion of steam through bitumen to reach the catalyst surface is controlled by its viscosity (L) and diffusivity coefficient of steam in bitumen (Dwb).

휇 푆푐 = 퐿 Equation 4- 7 휌퐿퐷푤푏

Stokes-Einstein equation (Equation 4-7) was used to calculate Dwb

퐷푤푏 = 푘퐵푇/(6휋휇퐿푅0) Equation 4- 8

-23 2 -2 -1 where, kB = 1.3806 X 10 m kgs k is the Boltzmann constant; and T, R0 and L are reaction temperature (K); radius of the water molecule (1.375 X 10-10 m) and bitumen viscosity, respectively, (Fogler, 1999).

Figure 4- 9: Diffusivity of Steam in Bitumen at Reactor Conditions

Diffusivity of steam in bitumen, Dwb is increase with increase in reaction temperature and decrease in the dynamic viscosity of the solvent. The linear relationship between DWB and T/ predicts diffusivity of water in bitumen at 25 °C is 2.34 X 10-14 m2/s which is four orders of magnitude lower than the CO2 diffusivity in bitumen at similar pressure (Reza Etminan, et al.,

2014). Schmidt number, Sc calculated using the steam-bitumen diffusivities are presented in

Table 4-9.

Table 4- 9: Schmidt Number at Different Reaction Temperatures

Reaction Temperature °C 350 360 370 380 390 Schmidt Number - 234 226 216 209 196

The decrease in Schmidt number with increase in reaction temperature suggests molecular diffusion of steam into the bitumen layer was increasing because of the reduction in the liquid phase viscosity (Naohisa, et al., 2016).

Reynolds number, Re is defined as the ratio of inertial force to viscous force to describe the fluid flow pattern(Fogler, 1999). Based on its values the flow is classified as laminar or turbulent flow.The increase in Reynolds number with increase in the reaction temperature is reflective of increase the thickness of the fluid boundary layer.

It is directly proportional to the particle diameter (dp) and superficial velocity (us) and inversely proportional to the kinematic viscosity () of the fluid. Gas and liquid phase Reynolds number not only predict the flow regime but are useful in calculating the other hydrodynamic properties such as pressure-drop and liquid holdup.

푑푝푢푠휌퐿 푅푒퐿 = Equation 4- 9 휇퐿(1−휖)

푑푝푢푠휌푔 푅푒퐺 = Equation 4- 10 휇푔(1−휖)

Figure 4- 10: Reynolds Number vs. Schmidt Number As shown in Figure 4-10, low bitumen flowrates resulted in extremely low liquid Reynold number (ReL). The decrease in Schmidt number indicates an increase in the thickness of the concentration boundary layer. This shows diffusion of steam in bitumen to reach the catalyst surface is adversely effected by the increase in the reaction temperature. The diffusion of steam in bitumen could be improved by increasing the water to oil ratio (WOR) and/or the reaction pressure.

4.8 Hydrodynamic Properties

The hydrodynamic properties i.e., flow regime evaluation, pressure-drop and holdups were evaluated at reaction conditions of 400 psig pressure and 350 °C to 390 °C temperature using the empirical correlations described in Section 2.7.6, Section 2.7.7 and Section 2.7.8 respectively for the best and worst performing catalysts; Cat J15 and Cat J17 respectively.

Table 4- 10: Effect of Catalyst Particle Size on Hydrodynamic Properties

Pressure Drop Liquid Holdup (Pore Flow Regime (psi/m) Volume Basis) Correlations Cat J15 Cat J17 Cat 15 Cat J17 Cat J15 Cat J17 Turpin and - 0 0 38 - 40 % 38 - 40 % Huntington Saada Two Phase 0.05 0.03 32 % 32 % Fukushima and Erroneous Results - Erroneous Results Kusaka

Turpin and Huntington reported three type of flow regimes (spray, bubble and slug) could exist in a packed bedreactor with cocurrent upflow of gaseous and liquid reactants but they did not provide any correlations that can be used to predict the flow regime. Because of the extremely low liquid Reynolds number, none of the Fukushima and Kusaka’s equations (Equations 2-42 to

Equation 2-49for flow regime evaluation and Equation 2-57 for liquid holdup) provided any reasonable results.Gas phase Reynolds number (ReG) was higher than the minimum gas phase

Reynolds number as described by Saada for the existence of the two-phase flow (Equation 2-41)

(Saada, 1972). The calculated pressure-drop (gl) for both Cat J15 and Cat J17 was extremely low as it was witnessed during the pilot experiments. The empirical correlations described by

Turpin and Huntington (Equation 2-56) indicates that the liquid holdup decrease from 40 vol.% to 38 vol.% with increase in the reaction temperature from 350 °C to 390 °C because of the variation in the gas and liquid phase flow rates. Liquid holdup calculated from Saada’s correlation (Equation 2-55) was 32 vol.% and no variation was noticed with change in the

Reynolds number.

Chapter 5: Conclusions and Recommendations

The successful demonstration of Aquaprocessing of bitumen to produce synthetic crude oil and pioneering the evaluation of reactor design parameters were the two novelties of the work presented in this manuscript. The experimental work conducted during this project was focused on evaluation of kinetic parameters required for reactor design for partial upgrading of bitumen via Aquaprocessing. For the first time, mass transfer effects and hydrodynamic properties for

Aquaprocessing of bitumen were evaluated at the reaction conditions. The key findings and recommendations for the future work are mentioned in this last chapter. The results presented in this thesis combined with findings from the future recommended work and heat transfer study would allow for effective scale up of this process.

5.1 Catalyst Particle Size and Preparation Technique

The identical physical and chemical characteristics of Cat H-2.1 and Cat H-2.2 catalyst as well as similar reduction in total acid number, viscosity, sulfur and vacuum residue content in SCO showed that the catalyst particle size has no impact on the overall catalyst performance when they were prepared via co-precipitation method.

CO2-TPD and NH3-TPD showed major difference in basicity and acidity, respectively between catalyst J15 and J17. Cat J15 (dp = 1.0 mm) consistently outperformed Cat J17 (dp = 2.5 mm) in total acid reduction and vacuum residue conversion. In case of Cat J17, external mass transfer was observed as a rate limiting step at reaction temperature of 380 °C or higher. These results highlight that catalyst particle sizes needed to be optimized when they were synthesized using the wet-impregnation method.

5.2 Improvement in Synthetic Crude oil properties and Economic Advantage

Cat J15was less active towards TAN reduction and sulfur removal than Cat H-2; however, it displayed similar activity in terms of vacuum residue conversion and viscosity reduction.

Because of the ease of preparation and significant reduction in active metal loading, Cat J15 is recommended for commercial applications. Aquaprocessing of bitumen at 390 °C and 400 psig at0.25 h-1 WHSV and 5 : 100 (m/m) water to oil ratio in the presence of Cat J15 produced synthetic crude oil with 80 % lower TAN, 98 % lower viscosity, 34 % lower vacuum residue content and 10 % lower sulfur content. Furthermore, modifying the textural properties of the support of Cat J15 may fulfil all the desirable properties of TAN and viscosity reductions, desulfurization and stability.

Based on above improvements in SCO properties, Aquaprocessing partial upgrading facility will have the net margin for the producers by US $ 9 – 11 /bbl. in comparison to the dilution techniques and would increase the bitumen carrying capacity for pipelines by 15%.

5.3 Packed Bed Reactor Design Equation

The rate of hydrocracking of vacuum residue fraction was verified as first order with respect to vacuum residue concentrations and the kinetic parameters obtained from the Arrhenius plots were true reflection of catalyst activity. The average activation energy for Cat H-2 was 28.8 kcal/mol. compared to 21.0 kcal/mol. for Cat J15. This 7.8 kcal/mol. difference was indicative of differences in the yield distributions obtained from the two catalysts. The simulated distillation data showed that Cat J-15 favored vacuum gasoil product over light and middle distillates in comparison to Cat H-2. The required weight of the catalyst J15 (W, kg) required to achieve

3 desired vacuum residue conversion (X) for a given volumetric flow rate of bitumen (v0, dm /h) at

84 reaction temperature (T, K) can be calculated using the following packed bed reaction design equation.

푣0 1 푊 = 10589 × ln − (1 − 푋) (8.94 × 105)푒 푇

To obtain conversions similar to those reported in this thesis, the reactor geometry needs to be selected such that dimensionless numbers like Reynolds number and Schmidt number are constant or at least partially constant.

5.4 Mass Transfer Limitation

Cat J17 prepared by wet-impregnation method, exhibited significant mass transfer limitations at

-7 higher reaction temperatures of 390 °C. Mass transfer coefficient (km)of 1.24 X 10 cm/s was determined for steam and bitumen system at 350 °C and 400 psig with 4.8 wt.% water in feed; it increased linearly with the rise in the reaction temperature. The decrease in Schmidt number with increase in reaction temperature indicates that the diffusion of steam in bitumen is decreasing because of increase in the thickness concentration boundary layer.

5.5 Hydrodynamics

The empirical correlations provided by a) Turpin and Huntington, b) Saada, and c) Fukushima and Kusaka were used for estimating the flow regime, pressure-drop and liquid holdup. The former two yielded similar data predicting less than 0.05 psi/m pressure-drop and between 38-40 vol.% liquid holdup while the latter one seems not to be applicable for the lab scale pilot plant operations.

5.6 Recommendations

1) The present work was carried out using a fixed bed reactor with cocurrent upflow of steam

and bitumen. It would be beneficial to conduct similar experiments using different reactor

configurations such as:

a) Fixed bed with cocurrent downflow of reactants to study the impact of back-mixing on

the reaction rates.

b) Testing these catalysts in a continuous stirred tank reactor (CSTR) could be indicative of

their performance in the ebullated bed reactors because the continuous mixing would

minimize mass transfer limitations; varying also the residence time would allow for better

understanding of the reaction kinetics and mass transfer limitations that were observed

while testing Cat J17.

c) Testing Cat J15 using two reactors in series would provide experimental data that will be

useful in the design of commercial reactor where two or more catalyst beds are used. A

provision should be made to collect the inter-stage products so the properties of the

product from both the reactors can be monitored.

2) The present work was carried out at 4 h residence time; it would be beneficial to extend this

study to different residence times to validate the kinetic data presented in this thesis.

3) Increasing the pore width and controlled incorporation of molybdenum sulfide could further

improve the activity of catalyst J15.

4) Prepare Catalyst J with particle size between 1 mm (Cat J15) and 2.5 mm (Cat J17) to find

the minimum catalyst diameter necessary for avoiding any mass transfer limitations.

5) Study the effect of increasing water to oil ratio and reaction pressure at higher reaction

temperature.

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Appendix A HAZOP Review

Table A- 1: HAZOP Summary for Feed Section

Table A- 2: HAZOP Summary for Feed Section

Table A- 3: HAZOP Summary for Separation Section

Appendix B

Experimental Data

Table B- 1: Data Summary for Cat H-2.1

Reaction conditions Average Reaction Temperature, °C 350 360 370 380 Pressure, Psig 400 400 400 400 Feed flow rate, ml/h 2.627 2.627 2.627 2.627 Water to Oil ratio, WOR (m/m) 5:100 5:100 5:100 5:100 Synthetic Crude Oil, SCO Characterization Products FEED SCO SCO SCO SCO Density kg/m3 1002.1 997.8 996.7 995.7 991.9 API ° 9.7 10.3 10.5 10.6 11.2 Dynamic Viscosity cP 67700 14498 7819 3573 1489 Carbon, C wt% 83.12 83.62 83.64 83.86 83.92 Hydrogen, H wt% 10.5 10.36 10.35 10.33 10.28 Sulfur, S wt% 4.11 3.48 3.45 3.37 3.37 Nitrogen, N wt% 0.39 0.42 0.43 0.42 0.43 Oxygen, O wt% 1.89 2.12 2.13 2.02 2.00 Total Acid Number, TAN mgKOH/g 2.34 0.67 0.24 0 0 P-Value 2.8 1.8 1.8 1.8 1.8 VR Fraction, 550 °C+ wt% 50.6 45.1 43 39.8 35.8 Conversions Dynamic Viscosity Reduction % 78.58 88.45 94.72 97.80 TAN reduction % 71.37 89.74 100 100 Vacuum Residue Conversion % 10.87 15.02 21.34 29.25 Sulfur Removal % 15.33 16.06 18.00 18.00

Table B- 2: Data Summary for Cat H-2.2

Reaction conditions Average Reaction Temperature, °C 350 360 370 380 Pressure, Psig 400 400 400 400 Feed flow rate, ml/h 2.627 2.627 2.627 2.627 Water to Oil ratio, WOR (m/m) 5:100 5:100 5:100 5:100 Synthetic Crude Oil, SCO Characterization Products FEED SCO SCO SCO SCO Density kg/m3 1002.1 997.8 997.2 995.9 987.7 API ° 9.7 10.3 10.4 10.6 11.8 Dynamic Viscosity cP 67700 23163 8898 2652 1065 Carbon, C wt.% 83.12 83.67 83.7 83.9 84 Hydrogen, H wt.% 10.5 10.39 10.35 10.33 10.36 Sulfur, S wt.% 4.11 3.57 3.49 3.33 3.24 Nitrogen, N wt.% 0.39 0.43 0.43 0.43 0.42 Oxygen, O wt.% 1.89 1.94 2.02 2.01 1.98 Total Acid Number, TAN mgKOH/g 2.34 0.52 0.21 0 0 P-Value 2.8 1.8 1.8 1.8 1.8 VR Fraction, 550 °C+ wt.% 50.6 44.9 43.1 39.5 36.6 Conversions Dynamic Viscosity Reduction % 65.79 86.86 96.08 98.43 TAN reduction % 77.78 91.03 100 100 Vacuum Residue Conversion % 11.26 14.82 21.94 27.67 Sulfur Removal % 13.16 14.96 18.96 21.17 99

Table B- 3: Data Summary Table for Cat J15

Reaction conditions Average Reaction Temperature, °C 350 360 370 380 390 Pressure, Psig 400 400 400 400 400 Feed flow rate, ml/h 2.627 2.627 2.627 2.627 2.627 Water to Oil ratio, WOR(m/m) 5:100 5:100 5:100 5:100 5:100 Synthetic Crude Oil, SCO Characterization Products FEED SCO SCO SCO SCO SCO Dynamic Viscosity cP 67700 23163 8898 2652 1065 1065 Sulfur, S wt.% 4.11 3.98 3.91 3.87 3.76 3.69 Nitrogen, N wt.% 0.39 0.39 0.39 0.40 0.41 0.42 Total Acid Number, TAN mgKOH/g 2.34 1.32 1.21 0.99 0.71 0.42 P-Value 2.8 1.7 1.6 1.6 1.6 1.5 VR Fraction, 550 °C+ wt.% 50.6 43.78 42.03 40.15 37.42 33.60 Conversions Dynamic Viscosity Reduction % 65.79 86.86 96.08 98.43 98.43 TAN reduction % 43.80 48.50 57.69 69.87 82.05 Vacuum Residue Conversion % 13.47 16.94 20.65 26.04 33.60 Sulfur Removal % 3.19 4.76 5.76 8.63 10.11

Table B- 4: Data Summary for Cat J17

Reaction conditions Average Reaction Temperature, °C 350 360 370 380 390 Pressure, Psig 400 400 400 400 400 Feed flow rate, ml/h 2.627 2.627 2.627 2.627 2.627 Water to Oil ratio, WOR(m/m) 5:100 5:100 5:100 5:100 5:100 Synthetic Crude Oil, SCO Characterization Products FEED SCO SCO SCO SCO SCO Dynamic Viscosity cP 67700 19245 6593.5 4613 1847 1007 Total Acid Number, TAN mgKOH/g 2.34 0.46 1.41 1.72 1.26 0.91 P-Value 2.8 1.7 1.7 1.6 1.6 1.6 VR Fraction, 550 °C+ wt.% 50.6 49.05 46.11 44.40 40.98 40.83 Conversions Dynamic Viscosity Reduction % 71.57 90.26 93.19 97.27 98.51 TAN reduction % 80.25 39.74 26.39 46.13 60.96 Vacuum Residue Conversion % 3.05 8.87 12.24 19.01 19.31

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Appendix C

Difference between the product distribution for Cat H-2.1 and Cat J15

This shows, Cat J15 was more selective towards the production of vacuum gasoil (VGO) than the light and middle distillates. One of the contributing factor towards the lower values for the activation energy for Cat J15.

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Appendix D

Predicted Fluid Properties by ProMax at Reactor Conditions

Table D- 1: ProMax Property Table for JACOS bitumen with Steam at 350°C

Total Vapor Light Liquid Water mass % 4.762 83.522 0.016 JACOS Bitumen mass % 95.238 16.478 99.984 Temperature °C 350 350 350 Pressure bar 27.579 27.579 27.579 Mole Fraction Vapor % 29.577 100.000 0.000 Mole Fraction Light Liquid % 70.423 0.000 100.000 Mole Fraction Heavy Liquid % 0.000 0.000 0.000 Molecular Weight kg/kmol 212.051 18.158 293.486 Mass Density kg/m^3 268.668 10.231 781.873 Molar Flow kmol/h 1.24E-05 3.66E-06 8.72E-06 Mass Flow kg/h 2.63E-03 6.65E-05 2.56E-03 Vapor Volumetric Flow m^3/h 9.77E-06 6.50E-06 3.27E-06 Liquid Volumetric Flow m^3/h 9.77E-06 6.50E-06 3.27E-06 Std Vapor Volumetric Flow m^3/h 2.93E-04 8.67E-05 2.07E-04 Std Liquid Volumetric Flow m^3/h 2.62E-06 6.65E-08 2.56E-06 Compressibility 0.420 0.945 0.200 Specific Gravity 0.627 0.783 API Gravity 3.677 Enthalpy kJ/h -3.958 -0.847 -3.111 Mass Enthalpy kJ/kg -1507.952 -12744.881 -1215.963 Mass Cp kJ/(kg*°C) 2.919 2.172 2.939 Ideal Gas CpCv Ratio 1.016 1.292 1.011 Dynamic Viscosity cP 0.02215 0.780 Kinematic Viscosity cSt 2.165 0.998 Thermal Conductivity W/(m*°C) 0.053 0.096 Surface Tension dyn/cm 19.020 Net Ideal Gas Heating Value MJ/m^3 346.159 0.254 491.438 Net Liquid Heating Value MJ/kg 38.214 -2.117 39.262 Gross Ideal Gas Heating Value MJ/m^3 366.734 2.142 519.862 Gross Liquid Heating Value MJ/kg 40.512 0.347 41.556

102

Table D- 2: ProMax Property Table for JACOS bitumen with Steam at 360°C

Total Vapor Light Liquid Water mass % 4.762 98.841 2.122 JACOS Bitumen mass % 95.238 1.159 97.878 Temperature °C 360 360 360 Pressure bar 27.579 27.579 27.579 Mole Fraction Vapor % 31.767 100.000 0.000 Mole Fraction Light Liquid % 68.233 0.000 100.000 Mole Fraction Heavy Liquid % 0.000 0.000 0.000 Molecular Weight kg/kmol 212.051 18.218 302.293 Mass Density kg/m^3 251.574 10.072 768.801 Molar Flow kmol/h 1.24E-05 3.93E-06 8.45E-06 Mass Flow kg/h 2.63E-03 7.16E-05 2.55E-03 Vapor Volumetric Flow m^3/h 1.04E-05 7.11E-06 3.32E-06 Liquid Volumetric Flow m^3/h 1.04E-05 7.11E-06 3.32E-06 Std Vapor Volumetric Flow m^3/h 2.93E-04 9.32E-05 2.00E-04 Std Liquid Volumetric Flow m^3/h 2.62E-06 7.17E-08 2.55E-06 Compressibility 0.442 0.948 0.206 Specific Gravity 0.629 0.770 API Gravity 4.104 Enthalpy kJ/h -3.881 -0.909 -2.973 Mass Enthalpy kJ/kg -1478.516 -12681.439 -1164.182 Mass Cp kJ/(kg*°C) 2.941 2.174 2.963 Ideal Gas CpCv Ratio 1.015 1.289 1.011 Dynamic Viscosity cP 0.02252 0.765 Kinematic Viscosity cSt 2.236 0.994 Thermal Conductivity W/(m*°C) 0.054 0.094 Surface Tension dyn/cm 17.930 Net Ideal Gas Heating Value MJ/m^3 346.159 0.362 507.150 Net Liquid Heating Value MJ/kg 38.214 -1.970 39.341 Gross Ideal Gas Heating Value MJ/m^3 366.734 10.952 828.711 Gross Liquid Heating Value MJ/kg 40.512 9.356 42.531

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Table D- 3: ProMax Property Table for JACOS bitumen with Steam at 370°C

Total Vapor Light Liquid Water mass % 4.762 98.382 1.965 Bitumen mass % 95.238 1.618 98.035 Temperature °C 370 370 370 Pressure bar 27.579 27.579 27.579 Mole Fraction Vapor % 33.613 100.000 0.000 Mole Fraction Light Liquid % 66.387 0.000 100.000 Mole Fraction Heavy Liquid % 0.000 0.000 0.000 Molecular Weight kg/kmol 212.051 18.300 310.150 Mass Density kg/m^3 237.474 9.931 752.657 Molar Flow kmol/h 1.24E-05 4.16E-06 8.22E-06 Mass Flow kg/h 2.63E-03 7.61E-05 2.55E-03 Vapor Volumetric Flow m^3/h 1.11E-05 7.67E-06 3.39E-06 Liquid Volumetric Flow m^3/h 1.11E-05 7.67E-06 3.39E-06 Std Vapor Volumetric Flow m^3/h 2.93E-04 9.86E-05 1.95E-04 Std Liquid Volumetric Flow m^3/h 2.62E-06 7.62E-08 2.55E-06 Compressibility 0.461 0.950 0.213 Specific Gravity 0.632 0.753 API Gravity 4.477 Enthalpy kJ/h -3.803 -0.960 -2.844 Mass Enthalpy kJ/kg -1448.914 -12603.977 -1115.666 Mass Cp kJ/(kg*°C) 2.964 2.177 2.988 Ideal Gas CpCv Ratio 1.015 1.286 1.010 Dynamic Viscosity cP 0.02290 0.747 Kinematic Viscosity cSt 2.305 0.992 Thermal Conductivity W/(m*°C) 0.055 0.093 Surface Tension dyn/cm 16.171 Net Ideal Gas Heating Value MJ/m^3 346.159 0.508 521.167 Net Liquid Heating Value MJ/kg 38.214 -1.774 39.408 Gross Ideal Gas Heating Value MJ/m^3 366.734 2.409 551.198 Gross Liquid Heating Value MJ/kg 40.512 0.688 41.702

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Table D- 4: ProMax Property Table for JACOS bitumen with Steam at 380°C

Table 4: ProMax Property Table for JACOS bitumen with Steam at 380°C Total Vapor Light Liquid Water mass % 4.762 97.780 1.832 JACOS Bitumen mass % 95.238 2.220 98.168 Temperature °C 380 380 380 Pressure bar 27.579 27.579 27.579 Mole Fraction Vapor % 35.182 100.000 0.000 Mole Fraction Light Liquid % 64.818 0.000 100.000 Mole Fraction Heavy Liquid % 0.000 0.000 0.000 Molecular Weight kg/kmol 212.051 18.408 317.158 Mass Density kg/m^3 224.820 9.810 726.318 Molar Flow kmol/h 1.24E-05 4.36E-06 8.02E-06 Mass Flow kg/h 2.63E-03 8.02E-05 2.54E-03 Vapor Volumetric Flow m^3/h 1.17E-05 8.17E-06 3.50E-06 Liquid Volumetric Flow m^3/h 1.17E-05 8.17E-06 3.50E-06 Std Vapor Volumetric Flow m^3/h 2.93E-04 1.03E-04 1.90E-04 Std Liquid Volumetric Flow m^3/h 2.62E-06 8.02E-08 2.54E-06 Compressibility 0.479 0.953 0.222 Specific Gravity 0.636 0.727 API Gravity 4.801 Enthalpy kJ/h -3.725 -1.003 -2.722 Mass Enthalpy kJ/kg -1419.114 -12509.007 -1069.743 Mass Cp kJ/(kg*°C) 2.989 2.192 3.015 Ideal Gas CpCv Ratio 1.015 1.282 1.010 Dynamic Viscosity cP 0.02327 0.727 Kinematic Viscosity cSt 2.372 1.001 Thermal Conductivity W/(m*°C) 0.056 0.091 Surface Tension dyn/cm 14.000 Net Ideal Gas Heating Value MJ/m^3 346.159 0.701 533.669 Net Liquid Heating Value MJ/kg 38.214 -1.517 39.465 Gross Ideal Gas Heating Value MJ/m^3 366.734 2.613 564.375 Gross Liquid Heating Value MJ/kg 40.512 0.944 41.759

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Table D- 5: ProMax Property Table for JACOS bitumen with Steam at 390°C

Total Vapor Light Liquid Water mass % 4.762 97.003 1.717 JACOS Bitumen mass % 95.238 2.997 98.283 Temperature °C 390 390 390 Pressure bar 27.579 27.579 27.579 Mole Fraction Vapor % 36.525 100.000 0.000 Mole Fraction Light Liquid % 63.475 0.000 100.000 Mole Fraction Heavy Liquid % 0.000 0.000 0.000 Molecular Weight kg/kmol 212.051 18.549 323.396 Mass Density kg/m^3 215.617 9.712 718.171 Molar Flow kmol/h 1.24E-05 4.52E-06 7.86E-06 Mass Flow kg/h 2.63E-03 8.39E-05 2.54E-03 Vapor Volumetric Flow m^3/h 1.22E-05 8.64E-06 3.54E-06 Liquid Volumetric Flow m^3/h 1.22E-05 8.64E-06 3.54E-06 Std Vapor Volumetric Flow m^3/h 2.93E-04 1.07E-04 1.86E-04 Std Liquid Volumetric Flow m^3/h 2.62E-06 8.39E-08 2.54E-06 Compressibility 0.492 0.955 0.225 Specific Gravity 0.640 0.719 API Gravity 5.084 Enthalpy kJ/h -3.646 -1.039 -2.607 Mass Enthalpy kJ/kg -1389.082 -12392.534 -1025.909 Mass Cp kJ/(kg*°C) 3.015 2.210 3.042 Ideal Gas CpCv Ratio 1.015 1.277 1.010 Dynamic Viscosity cP 0.024 0.706 Kinematic Viscosity cSt 2.433 0.983 Thermal Conductivity W/(m*°C) 0.056 0.089 Surface Tension dyn/cm 13.378 Net Ideal Gas Heating Value MJ/m^3 346.159 0.953 544.798 Net Liquid Heating Value MJ/kg 38.214 -1.185 39.514 Gross Ideal Gas Heating Value MJ/m^3 366.734 2.879 576.105 Gross Liquid Heating Value MJ/kg 40.512 1.275 41.807

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Table D- 6: ProMax Property Table for JACOS bitumen at 25°C

Total Vapor Light Liquid Water mass % 0.000 0.000 JACOS Bitumen mass % 100.000 100.000 Temperature °C 25 25 Pressure psi 15 15 Mole Fraction Vapor % 0.000 0.000 Mole Fraction Light Liquid % 100.000 100.000 Mole Fraction Heavy Liquid % 0.000 0.000 Molecular Weight kg/kmol 459.512 459.512 Mass Density kg/m^3 994.504 994.504 Molar Flow kmol/h 5.44E-06 5.44E-06 Mass Flow kg/h 2.50E-03 2.50E-03 Vapor Volumetric Flow m^3/h 2.51E-06 2.51E-06 Liquid Volumetric Flow m^3/h 2.51E-06 2.51E-06 Std Vapor Volumetric Flow m^3/h 1.29E-04 1.29E-04 Std Liquid Volumetric Flow m^3/h 2.50E-06 2.50E-06 Compressibility 0.019 0.019 Specific Gravity 0.995 0.995 API Gravity 9.713 9.713 Enthalpy kJ/h -4.261 -4.261 Mass Enthalpy kJ/kg -1704.452 -1704.452 Mass Cp kJ/(kg*°C) 1.763 1.763 Ideal Gas CpCv Ratio 1.013 1.013 Dynamic Viscosity cP 67588.269 67588.269 Kinematic Viscosity cSt 67961.796 67961.796 Thermal Conductivity W/(m*°C) 0.138 0.138 Surface Tension dyn/cm 37.923 37.923 Net Ideal Gas Heating Value MJ/m^3 787.628 787.628 Net Liquid Heating Value MJ/kg 40.248 40.248 Gross Ideal Gas Heating Value MJ/m^3 832.054 832.054 Gross Liquid Heating Value MJ/kg 42.538 42.538 Appendix E Contributions

Sukhdeep Gill – lab scale pilot design and construction, feed and product characterization, GC analysis, data analysis and manuscript writing Gerardo Vitale – catalyst preparation and characterization JACOS – provided bitumen

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Appendix F Copyright Permission for Figure 1-1

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